We still design businesses using an old industrial model of hierarchy. We make a single manager the central node of all information and decision-making on a quiet Tuesday. This architecture feels comfortable in calm waters. However, when the volume of decisions exceeds the cognitive capacity of that single human being, the system bottlenecks.

The sheer speed of modern knowledge work has far outpaced the processing capability of any individual manager. If you have spent years reprimanding staff for bypassing the chain of command, you cannot suddenly expect them to act like dynamic entrepreneurs during a crisis. Retreating into narrow lanes is a rational survival response to an environment that punishes structural deviation. We need systems where the people closest to the work have the information and autonomy to execute on behalf of the whole.

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Learning from the Hive

A colleague recently explored a biological metaphor that challenges our bias towards hierarchy. We automatically assume a beehive has a boss. We call the central figure the queen, implying executive authority. A honeybee colony does not rely on a conventional manager allocating each task. The queen does not direct day-to-day operations; she provides a biological anchor while remaining completely removed from operational decision-making.

The real work is entirely distributed. When foragers find a rich source of nectar, they return and perform the waggle dance to communicate the direction and approximate distance of the resource. Other foragers use this pure data sharing for their own evaluation. They do not simply accept instructions blindly; they use shared intelligence to assess the resources themselves. It is a masterclass in alignment without executive command.

This distributed capability is clearest during a crisis. Imagine a scorching summer afternoon where the temperature inside the hive rises dangerously. The colony does not convene a crisis management committee. Instead, workers instinctively increase fanning at the entrance to improve ventilation, while water collectors increase activity to aid evaporative cooling. The response emerges from workers changing behaviour based on shared environmental cues.

The Human Equivalent

Now look at the human equivalent. A major commercial product launch is failing on a Friday afternoon. The servers are crashing, payments are failing, and social media is angry. In a poorly aligned corporate structure, people wait for instructions. Software engineers point to infrastructure; marketing blames technical. The cognitive load on the senior leader becomes crushing as they act as a frantic dispatcher bridging hostile departments.

In a highly aligned team built on shared ownership, the response mimics the hive. A junior engineer diagnoses the application programming interface and updates the company in a public channel. A marketing manager reads that data and proactively pauses paid advertising. They do not wait for the chief executive. They feel the heat, understand the ultimate goal, and execute using their own judgement.

In my book Enhanced Leadership, I examine this exact tension between individual autonomy and strategic clarity. We say we want self-regulating networks, but we fail to provide the structural mechanisms to make them possible. This creates an apprentice gap in a distributed workforce. How do we teach junior members to interpret the environment accurately so they know when to act?

It is tempting to look at artificial intelligence as a magical shortcut. We rush to implement large language models, expecting technology to act as a digital waggle dance that solves communication overnight. Technology only ever amplifies the system you already have in place. It does not fix broken leadership. If your organisation is structurally siloed and driven by a culture of blame, AI will simply execute the wrong decisions much faster, automating dysfunction at scale. We must use these tools to strip away administrative burdens, freeing human capacity for the high-judgement work that actually drives a business forward.

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Implications for Leaders

How do we stop directing traffic and start building lasting structural capability? You have to move away from being the central processor of all information and become the architect of the system.

Audit your bottlenecks Look at every approval that crossed your desk in the last 30 days. Identify the structural blockages preventing your team from exercising their own judgement. Pushing authority down to where the information actually lives is essential. If you are consistently signing off on minor expenses while expecting your team to manage huge commercial client portfolios, you are actively infantilising them.

Engineer radical information transparency The biological network works because the workers have access to the same high-quality data. If strategic priorities and commercial pressures are locked in a boardroom, your team is navigating in the dark. Give them the commercial data they need. You cannot expect an employee to think like an owner if you treat them like a tenant.

Allow non-fatal failures You must deliberately allow for non-fatal failures to build long-term capability. When a team member makes a decision you would have made differently, do not immediately overturn their call. Review the data they had, explore their thought process, and coach their judgement.

Implications for Coaches

When working with senior leaders, pay attention to the language they use to describe their teams. If they frequently complain about a lack of initiative, explore their approval processes. Ask them to map out a recent crisis response. Who made the first move? Who waited for permission? Challenge them to identify where they might be acting as a dispatcher rather than an architect. Help them design small experiments to step back from operational decision-making and test the system’s resilience.

Operating at the Correct Altitude

The queen bee operates exclusively at the macro level. She anchors the system and trusts it to function. As leaders, we have to learn to operate at the correct altitude. Are you constantly dipping down into your team’s daily work, checking their maths, rewriting their emails, or asking for granular updates?

Experiment for one month by setting the conditions for success, ensuring the health of the organisation, and then getting out of the way. Are you building a team that requires your constant direction to function, or are you designing a system capable of solving problems you have not even anticipated?

Until next time, keep leading, keep learning, and keep levelling up!

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By Lee Whitmore

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I explored this tension recently on the podcast with Dave Reynolds, founder and CEO of the Rumin8 Group, a growth consulting firm that works with executive teams around the world. Dave put it simply: ‘the gap between success and failure is knowledge and application.’ A plan can be beautifully formulated and still fail, not because the thinking was wrong, but because nobody built ownership into the rollout.

That distinction matters more than most leaders realise. Strategy tells people what to do. Coaching culture determines whether they actually do it.

The Real Difference Between Directing and Coaching

Dave described coaching as ‘a two-way investment’, not a one-way transfer of knowledge from leader to team. His approach is deliberately Socratic: rather than teaching people something new, he uses questions to help them organise what they already know into something they can act on with confidence.

This is a subtle but important shift for leaders used to solving problems by telling. When a leader hands down a finished plan, the team receives instructions. When a leader builds the plan with the team, using questions to draw out their thinking, the team gains ownership. Dave’s experience across industries backs this up: organisations that create plans with their people, rather than for them, see far less resistance during implementation.

That single question, ‘did you create the plan with the team, or for the team?’, is one worth asking in your own organisation this week. It tends to expose exactly where execution problems come from.

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Where Strategy Actually Breaks Down

In Dave’s diagnostic work, the pattern that shows up again and again is a lack of self-awareness. Teams and leaders often believe they are communicating clearly, aligning well, and executing consistently. The reality inside the organisation frequently tells a different story. Silos form, communication gaps widen, and progress plateaus, usually because leaders have been directing and dictating rather than asking.

This connects directly to something I write about in Enhanced Leadership: authenticity is not what you say, it is the alignment between what you believe, what you say, and what you do. A leader can claim to value collaboration while every decision-making moment is a monologue. The team notices. Coaching culture closes that gap by making questions the default mode of leadership, not an occasional technique reserved for formal one-to-ones.

Dave also stressed a point that gets missed constantly: follow-up. A powerful coaching conversation with no accountability afterwards achieves very little. He described good coaching as ‘Chainlink’, where each session connects to the last through a simple check-in on what was committed to previously. Without that link, energy and intention evaporate, and accountability with them.

What This Means for Leaders

If you want to close your own gap between plan and execution, start by auditing how much of your leadership is spent asking versus telling. Leaders who default to giving answers create dependency. Leaders who default to good questions build capability, and capability is what allows a team to execute without you standing over every decision.

It is also worth being honest about how much time you invest in preparing for coaching conversations and following up afterwards. Dave found a direct correlation between preparation time and the value a coaching session delivers. Treat coaching as you would any other investment: input matters, and so does tracking the return.

Succession planning deserves the same honesty. Dave’s view, echoing Peter Drucker’s observation that culture eats strategy for breakfast, is that succession planning fails when it is treated as a strategy document rather than a cultural habit. Organisations that build career clarity and mentorship into everyday practice retain their best people far longer than those that scramble for a plan once someone hands in their notice. In exit interviews, the recurring theme Dave hears is not pay or workload, it is a sense that nobody was investing in the person’s future.

What Coaches Should Notice

For coaches working with senior leaders, Dave’s discovery process offers a useful model. Treat every organisation like a puzzle where half the pieces are still face down. Your job in the early conversations is not to offer solutions, it is to ask the questions that turn those pieces over: what has been a persistent challenge, for how long, and how self-aware is the leadership team of the real cause.

Watch for leaders who describe their plan as something they ‘rolled out’ rather than something they ‘built with’ their team. That language is often the clearest early signal of where resistance will surface later. And listen for what happens after a coaching conversation ends. If a client cannot tell you what was committed to last time, the accountability chain has already broken, and that is worth addressing before moving on to anything new.

A Simple Test for Your Own Leadership

The next time you finalise a plan, pause before you present it. Ask yourself whether your team helped build it or simply received it. That one question will tell you more about your likely execution success than any amount of additional strategic polish.

Coaching is not a soft add-on to leadership, it is the mechanism that turns knowledge into application.

Until next time, keep leading, keep learning, and keep levelling up!

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By Lee Whitmore

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That is the core idea here: internal communication is too often built around the communicator’s habits rather than the audience’s needs. In an age of constant change, that is no longer good enough.

The real problem

I hear this all the time: ‘We keep telling people, and they still do not know.’ Leaders send emails, hold town halls, publish updates, and still discover months later that key decisions have not been understood. That is usually treated as a volume issue, but volume is only part of the story.

A more useful way to look at it is through channel misalignment. In the transcript, the point is made that people are often overwhelmed less by the amount of information than by the fact that it arrives in the wrong format for the way they work and learn. That is a leadership issue, not an admin issue.

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Why format matters

The argument for multimedia communication is not about chasing trends or pretending every message belongs on video. It is about acknowledging how people learn. The transcript draws on multimedia learning research, including Richard Mayer’s work, to make a simple point: people generally understand more effectively when words and visuals work together, rather than words alone.

It also makes a practical point about cognitive load. A long, dense document might contain all the necessary detail, but still fail to help people make sense of what has changed and what they are meant to do next. Information is not understanding. A good leader has to design for comprehension, not merely transmission.

A three-tier model

The most useful part of the transcript is the three-tier model: awareness, understanding, and reference.

Awareness is the quick signal. It is the short, direct message that tells people something matters and they should pay attention.

Understanding is the fuller explanation, often best delivered through walkthroughs, conversations, or longer video.

Reference is the durable record, the document people can return to when they need precision, governance, or searchability.

That sequence matters. A short video can create awareness, a walkthrough can build understanding, and a written guide can provide reference. They are not competing formats. They are different jobs in the same communication system.

The short video debate

The transcript handles the short-form video debate well. Yes, there is real concern about endless scrolling, attention fragmentation, and the effects of heavy consumer short-video use. The cited research links higher levels of short-form video use with poorer attention and reduced inhibitory control. That concern should not be waved away.

But workplace communication is not the same thing as algorithmic entertainment. A 60-second internal update with a clear purpose and a defined next step is not an infinite feed designed to keep people hooked. Used well, short video is not a distraction mechanism. It is a precision tool.

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What leaders should do

The practical shift is simple, but it requires discipline. For each important message, ask what job it needs to do, who it is for, and what format will help them absorb and act on it. Then choose deliberately.

That means some messages should be a short camera-to-camera update from a leader. Some should be a longer walkthrough or podcast. Some should be a written guide or process map. The mistake is using the same format for everything simply because it is familiar.

This is also where leadership modelling matters. If senior leaders are willing to record short, direct updates, they make the format feel normal rather than experimental. That sends a stronger signal than another polished memo ever will.

The coaching lens

For coaches, this is a rich issue because it exposes pattern, not just process. A useful question is whether a leader’s communication choices serve the audience or their own comfort. Another is whether the organisation is confusing professionalism with formality.

I would also look for hidden bias in format preferences. Some leaders default to written documents because that suits them. Others rely on meetings and assume that is enough. In both cases, the real issue is usually the same: they are choosing what is easiest to produce, not what is easiest to receive.

Final thought

The most important shift is from broadcast to design. Once you see communication that way, you stop asking, ‘Have we said it?’ and start asking, ‘Have we made it possible for people to understand it?’ That is a much better leadership question.

Until next time, keep leading, keep learning, and keep levelling up!

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By Lee Whitmore

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I spoke recently with Rui Bashir, who leads global HR for a Fortune 500 multinational operating across more than 20 countries. What he shared reframed the whole conversation for me. His opening statement cut straight to it: AI rollouts in global organisations succeed when leaders focus on trust and authority, not just the technology. That is the part of the story most people are not telling.

The Wait That Looks Like Resistance

Rui made a point that I think every leader needs to hear. When a team appears to be resisting a new AI tool, they are almost certainly not refusing to learn it. They are doing something entirely rational: they are doing their own quiet calculation.

What might I lose? Whose role gets bigger? Do I still matter?

That is the trust question. Whether the team believes someone will handle those concerns fairly. The authority question is whether people whose roles are being changed were ever actually asked about it. When the answers to both questions are unclear, the team waits. And in most organisations, that wait gets read as resistance. The gap between what leaders are communicating and what the team is trying to figure out is where years of stalled momentum live.

The solution Rui describes is, in one sense, straightforward: explain the why and the how clearly, and momentum follows. But as Rui was quick to point out, that framing is easier to state than it is to execute, especially at scale.

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Same Strategy, Completely Different Outcomes

This is where the conversation genuinely surprised me. Rui’s perspective is shaped by two decades of sitting in rooms where global strategy meets local reality. He has watched identical rollouts land in completely different ways depending on geography, culture, and language, and he gave one of the most striking examples I have heard to illustrate it.

Take a single word: courage. In Anglo-American corporate culture, courage is the lone voice at the table, dissent as a virtue, someone who says the thing nobody else will say. In Portuguese, the equivalent word means something closer to collective resolve: you go to the front because everyone behind you goes with you. The lone voice is not courageous; it is suspect. In certain Spanish-speaking contexts, calculated restraint is the mark of a skilled leader. Knowing when not to speak is part of the skill. The courageous thing is sometimes what you do not say in the meeting.

Three languages. Three definitions. One word. Now design an AI rollout that asks teams to “speak up if they have concerns”, and three teams hear three entirely different things. One team complies. Another interprets the silence as deference to the metrics. A third performs adoption while quietly killing the initiative.

Same product, same training, same KPIs. Completely different outcomes. And the standard headquarters read is always a change management problem.

As Rui put it: the local team is not struggling with change. The local team is doing exactly what the culture taught them to do when they sense the calculation is not safe.

None of that nuance is in the standard AI rollout playbook.

The Diagnostic Gap

Beyond culture, Rui made another point that applies universally, whether you lead a team of five or a function spanning continents: the importance of diagnosis before intervention.

He offered a vivid illustration. Imagine two leaders who say exactly the same thing in the same way: “I cannot trust my own judgement.” Same words. Same energy. Completely different problems.

The first leader was promoted for technical brilliance and has never had to make a hard call under real pressure. They need practice: real decisions, real stakes, building the muscle from scratch. The second leader used to have that muscle. They built it over a decade of hard calls. Then years of being second-guessed and overridden wore it down. They do not need more practice. They need someone to trust them again, so they can trust themselves.

If you get the diagnosis wrong, you spend six months telling the first leader they are brilliant when what they actually need is to make the call. You push the second leader to make more calls when what they need is someone to say: that judgement was always sound, it just got beaten down. Either way, you make things worse.

Orchestration: What the Human Actually Does

As AI takes on more of the operational doing, Rui argues that the most important human skill is not using the tools, it is orchestrating them. He described orchestration as the allocation problem: where does direction need to be given rather than absorbed? Where does trust need to be granted rather than withheld? Where does courage need to be spent rather than saved?

AI will not make those distinctions. The human will. Most leaders are already making these calls every day, instinctively. The opportunity, as Rui sees it, is to make those judgements more visible and more deliberate, so that scarce human resources go to exactly the right place.

When I asked him what trust looks like in an AI-augmented team, his answer was clear: how you use the information AI generates either builds or breaks trust. And when you operate across cultures, that translation of information must preserve trust, or the whole initiative begins to fracture.

The Apprentice Gap

Rui also picked up on something I explore in depth in Enhanced Leadership: what I call the apprentice gap. AI is already taking away the operational, entry-level work that silently shaped how people learned to do the harder work above it. The note-taking, the data entry, the first drafts. These tasks felt like graft. But they were also the training ground.

Rui sees this playing out in real time. Jobs at every level are being reshaped. Companies are actively seeking AI-native skills. And if schools and universities do not start building AI literacy into their curricula at pace, the cost of that adjustment will be felt across society. The concern is not that AI makes people redundant. The concern is that it removes the ladder that taught people how to think, decide, and lead.

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For Leaders Right Now

If you are leading an AI rollout, Rui’s advice is to resist the temptation to treat it like any other change programme: train people, communicate, measure adoption. That works on the surface. What is going on underneath is trust and authority.

Before the announcement, before the training plan, ask yourself two questions. Do my people believe this will be handled fairly? And have the people whose roles are being changed actually been asked?

If you lead globally, add a third: what does this message mean in the room I am not sitting in?

For coaches, the pattern to look for is the leader who frames a team’s hesitation as resistance without ever asking what that hesitation is made of. The diagnostic question is not “how do we get them to adopt the tool?” It is “what calculation are they doing, and what are they not yet sure of?” The answer to that question changes everything about the intervention.

Until next time, keep leading, keep learning, and keep levelling up!

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By Lee Whitmore

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I believe we owe them both, and that the second part is in serious danger of being quietly neglected.

The Apprentice Gap

In Enhanced Leadership, I write about what I call the Apprentice Gap. This is the point at which we automate away so much of the routine work that used to serve as the training ground for junior people. The note-taking, the first draft, the screenshots, the sitting in silence in a room where decisions are being made. None of that was glamorous. But it was formative.

Those experiences taught people how organisations actually work. How decisions get made under pressure. Why context matters more than the process written on paper. If we remove all of that without being deliberate about what replaces it, we risk producing people who are technically capable but tactically shallow. They can use the tool, but they have not yet developed the judgement to know when the tool is needed, or when to override it.

That distinction matters enormously, and I do not think the leadership community is talking about it clearly enough.

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Career Stage, Not Age Category

Before going further, it is worth addressing something that can derail this conversation quickly. Whenever we talk about developing younger people, there is a pull towards stereotyping. Gen Z wants this. Millennials are like that. Before long, we are talking in slogans rather than paying attention to actual people.

I had a conversation with Tamara Miles on the podcast last year that stuck with me.

Her point, grounded in research, was that what matters most to people shifts depending on where they are in their career, not simply how old they are. Her framework of community, contribution, and challenge offers a much more useful lens than generational labels. Someone early in their career is usually most hungry for challenge, because that is what signals they are trusted and taken seriously. Someone further along may be more focused on contribution and legacy. Neither is absolute.

This matters because when we stop assuming and start noticing, we become better leaders. The minute we generalise based on age, we are making things easier for ourselves and poorer for the people we are supposed to be developing.

Agency Is Not a Token

Fred Miller raised a related point when he appeared on the podcast.

The difference between someone having agency and simply being given permission to act. You cannot hand someone agency as though it is a gift card. Your job as a leader is to create the conditions where people can actually use it.

That means clear guardrails, yes. But it also means not burying every small decision under layers of approval. If every judgement call has to be checked, corrected, and delayed by three levels of management, you are not building capability. You are training dependence. And a generation that arrives expecting to participate, to be developed, and to be taken seriously from day one will not stay in an organisation that treats them like a liability to be managed.

That is not entitlement. That is a reasonable expectation of a workplace that takes development seriously.

The Real Question for AI-Enabled Workplaces

Here is where I think the conversation gets difficult in a useful way. In an AI-enabled workplace, we have to be far more deliberate about learning experiences than previous generations were. The old model largely relied on osmosis. You sat near enough to the action, you absorbed how things worked, and gradually you developed judgement. It was rarely intentional, but it worked.

Now, if the machine does the note-taking, who learns by paying attention? If AI drafts the first version of everything, what does the junior person learn by doing? If systems handle scheduling, routine communication, and follow-up, how does someone learn to hold a conversation, read a room, weigh competing priorities, and make a decent call when the answer is not obvious?

These are not rhetorical questions. They are the real design challenge of leadership development right now. The answer is not to slow down AI adoption. The answer is to be intentional about what we build in its place. As I note in Enhanced Leadership, this might mean inviting junior colleagues into the room not to take notes, but to observe the decision-making process. It means narrating your thinking rather than just presenting your conclusions. It means externalising wisdom rather than assuming it will be absorbed by proximity.

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What Leaders Should Do Differently

The practical implication is straightforward, even if it takes effort. Audit your team’s development experiences. Not just the formal training, but the informal, daily moments where someone could be learning something real.

Ask yourself: are people being given challenge with appropriate support, as Tamara’s framework suggests? Or are they left to sink or swim, or alternatively, so insulated from real decisions that they never have to exercise any judgement at all?

Ask whether your use of AI tools is removing friction in a way that also removes learning. If so, what are you building in to replace that? Are your senior people visible in the way Fred described: showing what good looks like, rather than hiding behind emails and back-to-back meetings?

And ask honestly whether you are generalising when you should be observing. What stage is this person actually at? What would genuinely stretch them right now, without breaking them?

A Note for Coaches

If you work with leaders who are responsible for developing others, this is fertile ground. The question is rarely whether a leader cares about their team’s growth. Most do. The more useful question is whether their instincts about development have kept pace with how the workplace is actually changing.

Watch for leaders who default to the old osmosis model and are vaguely disappointed that it does not seem to be working any more. Help them see that the model itself has changed, not the people. The deliberate creation of learning experiences is now a leadership skill in its own right. Help them design for it rather than assume it will happen naturally.

Tool Fluency and Leadership Readiness Are Not the Same Thing

World Youth Skills Day is a useful prompt, but the question it raises is live every week, not just on a calendar date. Yes, we should be building AI literacy. Yes, we should be helping people develop digital confidence and the ability to use the tools that will shape their working lives.

But tool fluency and leadership readiness are not the same thing, and we should be careful not to mistake one for the other. The real work is developing people who can think, judge, communicate, and take responsibility when the situation is genuinely messy and the answer is not sitting in a prompt.

That has always been the work. In an AI-enabled world, it just requires more intention.

If you are leading a team, developing talent, or coaching someone through this, I would leave you with one question: where in your own organisation are you at risk of making assumptions when what you need to be doing is meeting the person in front of you, and working out what stage they are really in?

Until next time, keep leading, keep learning, and keep levelling up!

LevelUp

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By Lee Whitmore

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Most leaders can name the moment, if they are honest. The problem is that it rarely feels like a moment. It feels like a series of small, sensible choices that only reveal their full cost in hindsight.

I want to talk about that today. And I am going to use a coffee shop to do it.

The Theatre of the Syphon

There was a coffee shop in a town where I used to live. It was my favourite. Not the most convenient, not the biggest menu. My favourite, because they did syphon coffee.

If you have never seen syphon coffee made, it is worth looking up. Two glass chambers, a heat source, and a process that is part chemistry, part theatre. Water heats, pressure builds, and the liquid rises into the upper chamber where it meets the ground coffee. Then, as the heat is removed, the brewed coffee is drawn back down through a vacuum filter, clean and precise. The whole thing takes several minutes. It bubbles, rises, settles, and clears. Slow enough to watch. Deliberate enough to appreciate.

When done well, it produces a clean, remarkably expressive cup. But the experience communicates something beyond the taste: this is being made with care, and it is being made for you.

Human beings have always responded to ceremony. Think about the Japanese tea ceremony, or Chinese gongfu tea practice, where the precise sequence of movements is not a delay but the point itself. The ritual is the value. The same is true for cigar enthusiasts who use a wooden match rather than a lighter, not because it burns better, but because the intention matters. In each case, the ceremony signals: this is not ordinary, and you deserve this.

That coffee shop understood something many businesses do not. They were not selling caffeine. They were selling distinction.

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The Economics of Ceremony

Ceremony is expensive. Not only in money, but in time and throughput. A syphon coffee takes longer to prepare. It demands more attention. It occupies skilled hands for longer and slows the queue. When a business becomes popular, those constraints begin to bite.

The shop did the sensible thing first: they raised their prices. That was the right call. A premium product, a skilled process, and real demand. But at the volume they needed, the maths still did not work.

And that is one of the hardest truths in business. A product can be excellent. An experience can be memorable. A brand can be loved. And yet the operating model underneath can still be fragile.

So they stopped the syphon coffees. They moved to tableside French press, which was still distinctive. Then, as popularity grew again, the same pressure returned. Eventually, they became operationally much like every other coffee shop: espresso-based, faster to produce, easier to standardise. Still excellent. But no longer doing the thing that had made them stand out.

The Leadership Parallel

This is not a coffee story. It is a story about how market pressure reshapes business identity, often without anyone making a conscious decision to let it happen.

A specialism is not just a positioning choice. It is an operating choice. It affects pricing, capacity, service design, delivery speed, hiring, and margin structure. When leaders talk about differentiation, they often treat it as a branding question. It is not. It is an economics question.

If your offer is slower, more bespoke, more expert-led, or more manually intensive, then one of two things must be true. Either the price point has to justify that, or you have to accept lower volume. If neither of those holds, the market will push you towards standardisation, whether you plan for it or not.

This is what I think of as the Rolex and Casio problem. Rolex can do what Rolex does because the price point supports craftsmanship, scarcity, and a completely different economic model. It does not need to behave like Casio because it is not competing on the same terms. But most businesses entering a crowded market do not have that pricing authority yet. They do not have the brand equity, the margin cushion, or the established demand that would fund a fully specialist model from day one.

For most new entrants, the honest position is this: you often need to start closer to Casio before you can earn the right to operate like Rolex.

Where Leaders Come Unstuck

Where I see leaders and organisations struggle is in designing for the identity they want, rather than the market position they actually have. They build a high-touch, bespoke, time-intensive offer, price it below what would actually sustain it, and then wonder why growth creates pressure rather than reward.

In Enhanced Leadership, I explore how authenticity and purpose must be anchored in everyday action, including every decision and every silence. The same principle applies to your business model. If your specialism is genuinely who you are, then every commercial decision either reinforces or quietly undermines that. The erosion rarely arrives dramatically. It arrives as a series of reasonable compromises.

Three Questions for Leaders

So here are three questions worth sitting with, whether you are reviewing your own offer or working with a client on theirs.

Does the market value this enough to pay properly for it? Not in principle, but in practice. Are people actually buying it at a price that works? Aspiration and viability are different things, and confusing them is costly.

Can your operating model sustain the time and attention your specialism requires at scale? What happens when demand doubles? Does the model get stronger, or does it start to fracture? The answer to that question tells you a great deal about whether your distinctiveness is built into the economics or just grafted on top.

Are you building for distinction or for durability? Being honest about which one you are actually doing is the starting point for better decisions. Sometimes the right move is to deepen the specialism and raise the price to match it. Sometimes the right move is to simplify the model and protect your margins.

And sometimes the smartest structure is both: an efficient core that generates consistent revenue, and a premium specialist offer at the edges where the pricing and capacity genuinely support it.

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A Framework Worth Considering

That two-tier model is often the most practical answer for coaches, consultants, and service businesses. Keep a reliable, scalable offer at the centre. Protect a smaller, higher-value, more specialist practice for clients where the model actually works.

The key discipline is separating the two clearly, and not letting volume pressure slowly erode the premium tier. Which is precisely what happened to that coffee shop.

For Coaches

If you work with leaders on strategy, commercial positioning, or growth, this tension shows up regularly. Watch for the leader who describes their offer in terms of what they love doing rather than what the market will fund. Watch for the one who is proud of how bespoke and personal their service is, but is running at unsustainable margins.

The useful questions are not about aspiration. They are about structure. What is the operating model underneath the identity? What would it take to protect the specialism at scale? And crucially: is the decision to stay specialist a strategic choice or a resistance to the harder work of building a viable model?

Those are very different problems, and they need very different coaching responses.

The Broader Point

I still think about those syphon coffees. The theatre of it. The sense that something careful was being made, specifically for you. That feeling does not come from a standard flat white, however good. But I also understand why they stopped.

Your market position is not defined only by what you love doing, or what you do best. It is defined by what you can sustain, what customers will fund, and what your model can carry without quietly breaking. If you want the economics of scale, design for scale. If you want the value of specialism, charge for specialism. And if you want both, be disciplined enough to structure them separately.

That is where strategy stops being a conversation about identity and starts becoming something you can actually build a business on.

Until next time, keep leading, keep learning, and keep levelling up!

LevelUp

Get the weekly briefing that helps you navigate organisational chaos with clarity. From mastering difficult conversations to adopting AI without losing the human touch, LevelUp is your weekly guide to leading with confidence.

By Lee Whitmore

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Lee is a leadership coach and writes about AI reshaping organisations. His interest is what these tools ask of the person building them: thinking, judgement, leadership capacity no workflow can replace. https://substack.com/@leveluplee

Muhammad is a clear, concise thinker who helps founders and builders make sense of AI without the noise. Through 60 Words of AI, he brings a practical, stripped-back perspective on what is happening in the field and why it matters. https://substack.com/@muhammadziyan

Both believe AI output is only as good as what you bring. This is our attempt to be honest about what that looks like.

Q1: We have both argued 2026 marks a shift - from using AI to building with it. What has that shift required?

Q2: We have both said AI output is only as good as what you bring. What does that require before opening the tool?

Subscribe to LevepUp Leadership (Lee)

Q3: Agents went live this year. Work is automated at role level, not just task level. What does that mean for humans still in the room?

Subscribe to 60 Words of AI (Muhammad)

Q4: The internet is filling up with content that sounds fine and means very little. What is our defence against contributing to that?

Q5: What do we know now about working with AI that we wish we had understood at the start?

Closing Thoughts

AI does not remove the need for judgement. If anything, it makes judgement more visible, because the machine can move quickly only after a human has decided what matters.

That is the shift we keep coming back to: from using AI well to building with it deliberately. The difference is not in speed or output alone, but in judgement, clarity, and the willingness to bring a point of view. That is what will separate the people who simply use these tools from the people who actually shape what they make with them.

About the Authors

Lee Whitmore is a leadership coach, author, and podcast host specialising in AI, strategic disruption, and major change programmes. His book, Enhanced Leadership, is available at https://mybook.to/EnhancedLeadership Find his newsletter at:

LevelUp Leadership

Get the weekly briefing that helps you navigate organisational chaos with clarity. From mastering difficult conversations to adopting AI without losing the human touch, LevelUp is your weekly guide to leading with confidence.

By Lee Whitmore

Muhammad Ziyan writes 60 Words of AI on Substack, covering everything happening in AI in 60 words or less. He writes for founders and builders who want AI made simple. Find his newsletter at

60 Words of AI

The world’s first AI newsletter that tells you everything happening in AI in just 60 words.

By Muhammad Ziyan

A trigger warning applies to this article. It contains references to suicide and mental health crisis. If this is a difficult subject for you right now, please take care of yourself first. Support resources are listed at the end.

There is a moment Steve Phillip describes that is hard to forget. A man called Richard is called into an HR office, told he is being suspended over a historical complaint, handed a leaflet about the Employee Assistance Programme, and sent on his way into a dark, wet November evening. No one checked whether he understood the document in his hand. No one asked how he was. No one paused long enough to notice what was unfolding.

Richard did not make it home.

Steve shared that story with me on the Level Up Leadership Podcast, recorded in recognition of World Wellbeing Week. Steve is the founder of the Jordan Legacy CIC, a community interest company focused on practical, collaborative solutions to suicide prevention. He founded it following the death of his son Jordan to suicide in December 2019. He brought it to the conversation not as a tragic anecdote, but as a precise and uncomfortable illustration of what happens when organisations mistake compliance for care.

The Tick-Box Trap

Most organisations, if asked, will tell you they take mental health seriously. They have mental health first aiders. They have a wellbeing policy. Some even have a specific protocol for what happens if an employee dies by suicide. And yet, as Steve pointed out, very few have genuinely embedded wellbeing into the daily culture of how they operate.

The gap is not one of intention. It is one of execution. Writing a policy is a decision made in a meeting room. Culture is what happens in every corridor, every performance review, every difficult conversation a manager has on a Tuesday afternoon when they are tired and unsure and the person in front of them is clearly not alright.

Steve draws on a principle he calls the ‘do no harm’ approach, borrowing the spirit of the Hippocratic oath. The idea is that before any policy, procedure, or performance process is introduced, leaders should ask: how will this land? Is there any risk to the wellbeing of anyone involved? And if so, what mitigation exists? It is a deceptively simple filter, but most organisations have never applied it.

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The Human Cost Has a Price Tag

One of the most striking points Steve made was about the economic case for getting this right. Suicide deaths are estimated to cost the UK economy around £10 billion per year. Deloitte has consistently reported that for every pound invested in workplace wellbeing, organisations see returns of around five pounds through reduced absenteeism, lower staff turnover, and improved productivity.

The moral imperative is obvious. But for those who need to make the business case to a board, the numbers are there. This is not a soft issue sitting on the edges of an HR agenda. It is a strategic one.

Yet Steve’s concern is that even where organisations are investing in training, they are not asking whether it is actually changing anything. Mental health first aid training is valuable. But if the line manager who completed that training still does not know how to sit with a colleague who is struggling, the training has not done its job.

A Framework Any Leader Can Use

One of the most practical things Steve shared was a simple conversational framework known as TED: Tell, Explain, Describe. When a conversation takes a concerning direction, instead of reaching for a yes-or-no question or defaulting to the ever-deflectable ‘how are you?’, a leader can simply ask three open questions.

Tell me what is going on for you right now. Explain to me so I can better understand. Describe to me how this is impacting on you.

These questions do not require clinical expertise. They require presence, eye contact, open body language, and a genuine willingness to hear the answer. What they do is open a door. They give the person in front of you somewhere to go. And, as Steve notes, they are far less frightening to ask than they might seem at first. He encourages leaders to practise saying them out loud, alone if necessary, just to get familiar with the words.

That advice resonated with me. I watched a clip of Steve delivering this framework in a TEDx talk, and I found myself saying the words aloud in an empty room. It was uncomfortable. Which is precisely the point: if we find it uncomfortable in private, we need to build our familiarity before we find ourselves needing it in a real conversation with someone in crisis.

Men, Masculinity, and the Cost of Presenting Too Late

75% of all recorded suicide deaths in the UK are men. The reasons are complex, but one of the most significant is that men tend to present much later in a mental health crisis. Stigma, the pressure of masculine identity, and a reluctance to ask for help all contribute to a pattern where men reach out only when things have become acute.

The implication for leaders is clear. If you are waiting for someone to come to you, you may be waiting too long. Regular, genuinely informal one-to-one conversations, not appraisals, not performance reviews, but human check-ins that include questions about capacity, about relationships within the team, about how someone is doing in the fullest sense, create the conditions where people can speak sooner. Monthly, even briefly, those conversations can shift the dynamic from reactive to preventive.

Culture is Not a Programme

This connects to a broader argument that runs through my own book, Enhanced Leadership, and through much of what Steve said. Psychological safety is not a document you file with HR. It is not a training course you complete once a year. It is the sum of small human interactions, daily decisions about how you speak to people, how you handle bad news, how you treat someone at their lowest point. In Enhanced Leadership, I describe this as the alignment between what you believe, what you say, and what you do. Steve would recognise that framing immediately.

The story of Richard is not a story about a bad organisation. It is a story about a process that was followed without the human layer that should accompany it. A five-minute conversation, asking whether Richard understood the EAP leaflet, asking whether there was anything immediately useful in it for him, acknowledging that this was difficult news, could have changed the outcome. It did not need to be lengthy. It needed to be human.

On Remote Working and Real Connection

I raised the question of remote and hybrid working with Steve, and his response was characteristically practical. His view is that mandating a return to the office is, at this point, largely a missed opportunity: the hybrid world is here and organisations need to adapt to it rather than resist it. The more useful question is what can be co-created with employees to help them feel genuinely connected. A buddy system, a standing wellbeing conversation, a culture where asking ‘how are you?’ means something. Steve’s suggestion is worth taking seriously: ask your people what would make them feel more connected, and listen to the answers.

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For Coaches

If you work with leaders and managers, this episode surfaces a pattern worth exploring with clients. Many leaders have the right values but not yet the language or confidence to act on them when it matters most. They know they should check in. They know the culture should be different. But in the moment, uncertainty takes over.

Useful questions to bring into a session might include: when did you last have a genuinely informal one-to-one with each member of your team, one that was not performance-related? How would you respond if a team member disclosed that they were having thoughts of suicide? What does your organisation’s EAP actually offer, and could you explain it clearly to someone in distress?

The TED framework is also worth introducing directly to coaching clients. It is accessible, memorable, and practical. It gives leaders a starting point when they feel at a loss for words.

A Message Worth Keeping

Steve ended our conversation with something Desmond Tutu is remembered for: we need to stop pulling people out of the river and go upstream to find out why they are falling in. That principle, applied to business, means building the conditions where people do not reach crisis point before they feel able to speak.

Most suicides are preventable. That is not a platitude. It is a finding grounded in research and evidence. And early, honest, human conversation is one of the most powerful tools available. Any leader can offer that. It costs nothing except the willingness to show up as a human being first.

Until next time, keep leading, keep learning, and keep levelling up!

LevelUp

Get the weekly briefing that helps you navigate organisational chaos with clarity. From mastering difficult conversations to adopting AI without losing the human touch, LevelUp is your weekly guide to leading with confidence.

By Lee Whitmore

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This is what I want to explore in this issue. Not busyness in general, but a specific and costly version of it: the tendency to pour resource and effort into the most visible part of a problem, while the actual constraint sits quietly elsewhere, untouched.

The Idea Behind the Framework

Back in 1984, a physicist-turned-management-thinker named Eliyahu Goldratt published a book called The Goal. It was written as a novel, which is an unusual choice for a business book, but it remains one of the most practically useful works in the genre. His central idea, the Theory of Constraints, is built on something deceptively simple.

Every system has a bottleneck: a single point that limits the output of the whole. And here is the part that matters most. It does not matter how efficiently everything else is running. If you are not addressing that bottleneck directly, you are not improving the system. You are adding pressure to a pipe that is already blocked.

The difficulty is that the bottleneck is rarely the most visible point of failure. It is often embedded in something politically sensitive, technically complex, or simply uncomfortable to examine. So organisations go somewhere else. They add resource to a part of the system that is already flowing reasonably well, launch initiatives that look energetic and impressive, and call that progress. Activity is not the same as impact.

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A Story About Apples

Picture a family-run apple farm in rural Somerset. Good orchards, healthy crop, and a persistent problem: roughly half the fruit they sent to market was arriving bruised, damaged, or late. The reason was the farm track, a rough dirt road full of ruts that battered every load before it reached the highway.

The family’s response was logical on the surface. If you are losing fifty percent, grow more. Double the harvest and you will be ahead even with the losses. So they planted more trees, hired more pickers, and sent more lorries down the same broken road. What followed was not recovery. The loads were heavier, the drivers pushed harder, the bruising worsened, and the attrition rate climbed from fifty percent to seventy. The barns filled with rotting fruit.

Eventually, someone stepped back and looked at the whole picture. Not the picking. Not the storage. Not the market strategy. The road. They made a counter-intuitive decision: they reduced the harvest deliberately, cutting volume back to premium-only fruit. The lighter loads travelled more gently, the attrition rate fell, and they finally had the breathing space to resurface the track. Once they did, they could ramp up again with a system that could actually handle it.

The lesson is not that you should always do less. The lesson is that sometimes the most productive move is to slow the pipeline while you fix the bottleneck. That takes nerve, because it looks like retreat. It is not. It is precision.

Where This Plays Out in Organisations

This pattern repeats itself across industries with striking regularity. Three examples show the same underlying dynamic, each wearing a different face.

In software development, a team under pressure to deliver faster brings in more developers. Code is written at speed. And yet delivery slows, the backlog grows, and frustration mounts. The bottleneck was never in development. It was in the quality assurance and testing function, a fraction of the size. Every developer added simply fed more work into an already-overwhelmed queue. The fix is not more developers; it is more testing capacity, and a sensible limit on how much development work can be pushed forward at once.

In recruitment, an organisation losing candidates between offer and start date responds by expanding the pipeline. More campaigns, more interviews, more volume at the front end. But a bigger pipeline flowing into the same blocked vetting stage simply means longer waits. Candidates who would have waited six weeks will not wait fourteen. The attrition rate increases, and the organisation keeps investing heavily in activity that is compounding the problem rather than resolving it.

In retail, a national chain with healthy footfall and strong basket sizes is losing revenue to poor conversion. More promotions are launched, more staff added to the floor, more visual merchandising invested in. The problem persists. The customer journey data, when someone finally looks at it properly, shows that people are abandoning full baskets at the checkout. The wait times are too long, the self-service machines unreliable. Everything upstream is performing well and being further invested in, while the actual point of failure goes untouched. Fix the checkout and revenue recovers almost immediately, not through clever strategy, but through finally targeting the constraint.

Why Leaders Avoid the Bottleneck

If the logic is this clear, why does the pattern repeat itself so persistently? There are a few honest reasons worth naming.

The first is visibility. The constraint often sits where the difficult, politically sensitive, or technically complex work lives. Addressing it means challenging existing processes, redirecting resource from activity that looks good on paper, and telling people that the busy, visible thing they are doing is not the most important thing. That requires a kind of courage that does not always get short-term recognition.

The second is that misdirected activity still feels like progress. In organisations with strong accountability cultures, doing something is always more comfortable than pausing. Leaders receive credit for launching campaigns, increasing headcount, showing urgency. That is a deeply human dynamic, and pretending otherwise does not help anyone.

The third is that the constraint is not always obvious without proper analysis. The apple farm family genuinely believed more picking was the answer. They were not foolish; they simply lacked visibility of the whole system.

In Enhanced Leadership, I write about the pull that many leaders feel back towards familiar, technical work when things are under pressure. The harder discipline is to lift your head, look at the whole system, and ask an honest question: where is the constraint, and am I pointing effort at it, or am I doing more of what I already know how to do?

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What Good Looks Like in Practice

Leaders who navigate this well tend to share a few qualities. They are curious about the whole system. They ask where things are slowing down, where the queue is building, where the attrition is happening. They look for the pile of rotting apples rather than celebrating the speed of picking.

They also resist vanity metrics: any measure that looks impressive but does not reflect progress on what actually matters. Number of applications received is a vanity metric if the constraint is processing speed, not volume. Lines of code written is a vanity metric if the bottleneck is testing. Promotions launched is a vanity metric if customers are abandoning at the checkout. The useful question is always what does this metric actually tell us about system flow?

And they are willing to be diplomatically direct. When the constraint sits in a difficult place, the effective leader does not pretend it is somewhere more convenient. They name it carefully, frame it constructively, and make the case for why it deserves attention. That is strategic clarity combined with good communication, and it is one of the most valuable things a leader can offer their organisation.

A Note for Coaches

If you work with leaders, this framework surfaces some rich territory. The most common pattern to watch for is a client who is genuinely working hard, fully committed, and still not moving the needle. The instinct is often to work harder on the same things. Before helping them build a better plan, it is worth asking: have they identified the actual constraint, or are they just adding lorries to a broken road?

A few questions worth exploring in session: where is the queue building in their team or organisation right now? Which part of the system is the bottleneck, and why has it been left unaddressed? What would it take to slow the pipeline temporarily in order to fix the underlying problem? And what would they need to say, to whom, to make that case?

The answers are often already present. What is missing is the permission to look at the uncomfortable place.

The Question to Sit With

Before you close this, take a moment with this question.

Think about the problem in your organisation that has the most resource pointed at it right now. The most activity, the most budget, the most visible effort. Ask yourself honestly: is that effort aimed at the actual constraint? Or is it aimed at the part of the problem that is most visible, most familiar, or most comfortable to work on?

If you are not sure, finding out might be the most important thing you do this week.

If this has been useful, I would love it if you passed it on to a colleague who is working hard on a problem that does not seem to move. Sometimes the missing piece is simply knowing where to look.

Until next time, keep leading, keep learning, and keep levelling up!

LevelUp

Get the weekly briefing that helps you navigate organisational chaos with clarity. From mastering difficult conversations to adopting AI without losing the human touch, LevelUp is your weekly guide to leading with confidence.

By Lee Whitmore

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Most of us have a default playlist of voices we trust, perspectives that feel familiar, and content that confirms what we already believe. It feels productive. It feels like development. But there is a quiet cost to that kind of curation: your judgement stops growing. And in a world that is moving as fast as ours is, comfortable thinking is a liability.

I want to talk about using podcasts not as passive inspiration, but as a form of active, deliberate leadership development. More specifically, I want to recommend three podcasts I listen to personally. I have chosen them not because they all agree with each other, but precisely because they do not.

The Case for an Uncomfortable Listen

I make the argument that leaders need to be more intentional about the inputs that shape their thinking. We are living through a period of rapid, irreversible change. What you feed into your mind matters. If your information diet is too narrow, too comfortable, or too self-affirming, your capacity for genuine judgement quietly erodes.

The same applies to podcasts. The goal is not to find one philosophy and adopt it wholesale. The goal is to listen to multiple credible voices, including ones that push back on your current thinking, and to build your own internal compass from that richer material.

With that framing in mind, here are the three I want to recommend.

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Coaching Real Leaders with Muriel Wilkins

https://www.murielwilkins.com/podcast-coaching-real-leaders

Muriel Wilkins is an executive coach, and her podcast runs under the Harvard Business Review banner. The premise is simple and bold: each episode is a real coaching session, recorded live, with a leader working through a genuine career or leadership challenge.

These are not role plays. They are not polished keynotes. They are real conversations, sometimes messy, sometimes emotional, always thoughtful. If you are a coach, this is as close to a masterclass as you will get in a podcast format. You hear contracting in action, the moment of reframe, the choice to probe or to sit in silence. You hear how Muriel helps a client move from fog to clarity by surfacing the real issue beneath the presenting one.

If you are a leader rather than a coach, it is equally valuable. You hear people like you working through familiar territory: stalled progression, imposter feelings, difficulty receiving tough feedback. You hear what it sounds like to think a challenge through properly.

There is a reason I recommend this show particularly to sceptical leaders, those who suspect that coaching is either vague or simply advice dressed up in questions. Three episodes of this podcast will test that assumption against real evidence. You will hear how focused and outcome-oriented a good coaching conversation can be, and how much ownership sits with the person being coached, not the coach. Coaching is not done to you. It is done with you, and this show demonstrates that clearly.

No Bulls*** Leadership with Marty Moore

https://yourceomentor.com/leadership-podcast/

Marty Moore is a former CEO with a long track record in senior leadership and a Wall Street Journal bestselling author. His show is positioned plainly: it is for leaders who want to be exceptional and are prepared to hear strong views about what that requires.

One of the central ideas Marty returns to consistently is single point accountability. The argument is straightforward. You cannot have effective execution without someone who is clearly and personally accountable for an outcome. Spreading accountability too thinly creates drift. Decisions stall. People confuse being busy with being effective. This aligns closely with my own experience, and with arguments I make in Enhanced Leadership about the conditions needed for both autonomy and performance to coexist.

I want to be honest about where his style stretches me, because I think that is exactly why it is worth listening to. Some of his positions can feel absolute. He often stakes out a very firm end of the spectrum: high standards above comfort, accountability above consensus. For some listeners that will feel like home. For others it will feel a little stark.

And that is precisely the point. You can treat his perspective as one end of a continuum. You might listen to an episode, find his stance a bit strong for your context, and still decide you want to move a couple of notches in that direction. That kind of deliberate, conscious calibration is what good development looks like.

The Productivity Show from Asian Efficiency

https://www.asianefficiency.com/our-podcast/

Asian Efficiency was founded by Thanh Pham in 2011, and The Productivity Show has become one of the longest-running podcasts in its category. Thanh’s own story is worth noting: a high school dropout who built a company that has helped tens of thousands of clients improve how they use their time and energy.

The show’s philosophy is practical and systems-oriented. You get detailed models, frameworks, and step-by-step approaches covering time-blocking, weekly reviews, email management, and prioritisation. Importantly, one of the underlying principles is that happy people are productive people. If you structure your work and life in ways that support your wellbeing, your output improves naturally.

That sits in deliberate tension with some of Marty’s harder-edged messages, and I think it is healthy to hold both threads at once. Leaders need to create clarity, drive performance, and hold people to account robustly. Leaders also need to recognise that humans are not machines, and that the quality of people’s energy and attention has a direct impact on results. Listening to both shows gives you a richer mental model of that tension rather than a false resolution of it.

In Enhanced Leadership, I argue that in an AI-driven world, time and attention are among the few levers that cannot be automated. That makes deliberate productivity thinking a genuinely strategic concern for leaders, not just a personal efficiency habit.

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A Note for Sceptics

Some time ago, I was asked to coach a leader who arrived as what I can only describe as an involuntary client. Their manager had put them forward. They told me plainly that coaching could not work for them, because they needed to be taught and shown, not asked questions. I did not try to argue the case. I suggested they give themselves three episodes of Muriel Wilkins and report back.

I tell that story because it matters how you approach these recommendations. The most value comes not from listening as a fan, but as a curious observer. Notice where a leader starts in an episode and where they end. Notice what shifts. Let the evidence do the work.

Similarly, if you tend to prioritise harmony above almost everything else in your leadership, spend time with Marty’s show. If you are someone who feels their workload is simply unmanageable and that no system could make a real dent in it, test that belief against a few episodes of The Productivity Show. Commit to three episodes of whichever one feels least comfortable. Treat it as an experiment.

Practical Implications for Leaders

The central question here is not which podcast to follow. It is whether you are being deliberate about the inputs that shape your thinking as a leader.

If the honest answer is that your current listening diet is largely self-affirming, that is worth addressing. You do not need to agree with everything you hear. You need to be sharpened by it.

A useful exercise: identify which of these three shows feels most at odds with your current default. Then listen to three episodes of that one specifically. Notice where you resist, where you are persuaded, and where you decide to move. That is your learning, not mine.

For Coaches

If you work with leaders, consider recommending these shows as pre-session listening. Clients who arrive having already engaged with a topic tend to be ready to go deeper faster. You might also use contrasting episodes from different shows as a way to surface a client’s values and assumptions, particularly around accountability, performance standards, or wellbeing. Asking “where do you sit on the spectrum between these two perspectives?” can open up territory that a direct question might not reach.

The question I want to leave you with this week is this: which of these three podcasts is furthest from your current thinking, and what might you gain by deliberately listening to three episodes of it rather than the one that already feels familiar?

If this kind of article, a slight departure from the usual format, is useful to you, I would genuinely like to know. You can leave a comment below.

Until next time, keep leading, keep learning, and keep levelling up!

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Get the weekly briefing that helps you navigate organisational chaos with clarity. From mastering difficult conversations to adopting AI without losing the human touch, LevelUp is your weekly guide to leading with confidence.

By Lee Whitmore

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The reason is usually straightforward, but it is easy to miss when you are focused on the numbers. Performance is an outcome. It sits at the end of a chain of cause and effect. When leaders jump straight to managing the output without examining what produced it, they are treating a symptom and leaving the underlying condition entirely unaddressed.

The distinction between managing performance and managing the drivers of performance sounds subtle. It is not. Confusing the two is one of the most common, and most costly, mistakes I see in complex, fast-moving organisations.

What Over-Managing Output Looks Like

Over-managing the output tends to produce short-term compliance and long-term erosion. People respond to the pressure. They tighten up, hit the number this week, perhaps by cutting corners or deferring harder work. But nothing in the system has changed, so nothing sustainably improves.

Over time, something more damaging sets in. When people feel continually judged on outputs without feeling supported in the process, trust erodes and energy dips. The most capable people, the ones with options, start looking elsewhere. And the leader ends up in a cycle of managing underperformance rather than building performance.

Accountability matters. I write about this directly in Enhanced Leadership: clarity, standards, and the human foundations of great leadership all require that leaders hold the line. But accountability without support is pressure, not leadership. Support without accountability is avoidance. The question is whether you are doing both, and in the right order.

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The Five Real Drivers

When performance is lagging, the right first question is not ‘why is this person not delivering?’ It is: ‘what conditions are shaping their ability to deliver?’ That shift in framing changes the quality of every conversation that follows.

Clarity. Does this person genuinely understand what is expected, not just the task, but the standard, the context, and the priority? Unclear expectations are one of the most common causes of underperformance, and they are entirely within the leader’s control to address. I am consistently surprised by how often a leader believes they have communicated clearly, while the person receiving that communication has a significantly different understanding of what they were asked to do.

Capability. Does this person have the skills, knowledge, and tools they actually need? This is frequently glossed over during periods of change. We place people in new situations, hand them new responsibilities, and then manage them on outputs before the capability has been built. That is a development gap wearing the costume of a performance problem.

Energy. This one is rarely spoken about directly, but it is critical. Workload, stress, burnout, personal circumstances, the relentless pace of change: all of these affect output quality, and none of them appear on a performance dashboard. I worked with a leader who was puzzled by a long-serving team member’s declining performance. When we dug deeper, the picture was clear: overwhelming workload, feeling unsupported through a restructure, and a quiet loss of belief that effort would lead anywhere. Addressing the performance directly, without addressing those conditions, would have been pointless and probably damaging.

Trust. When psychological safety is low, people manage upward. They tell you what you want to hear. Problems stay hidden until they become crises. A leader can read a set of progress reports that bear almost no resemblance to what is actually happening on the ground.

Feedback. Not the annual review kind. The ongoing, real-time signal that helps people course-correct as they go. When feedback only appears as criticism after something goes wrong, people either play it safe or keep doing the wrong things simply because nobody has told them clearly enough.

And then there are the structural drivers: systems, processes, workload, environment. Sometimes performance is low because the system people are working within is genuinely broken. No amount of one-to-one performance management will fix a broken process.

What Good Looks Like in Practice

A team is consistently missing its weekly delivery targets. The manager holds a team meeting about the targets. More pressure, more visibility, more accountability. Nothing changes.

The leader who manages the drivers does something different. Before any formal conversation, they spend time genuinely understanding the picture. They ask: what is getting in the way? What do you need that you do not currently have? Is the workload realistic? Is the brief clear? They examine the process end to end.

What they typically find is not that people are not trying. What they find is a combination of unclear priorities, inadequate tools, some team members overloaded while others are underutilised, and a culture where people are not comfortable raising problems early. None of that shows up in the weekly metrics. Fix those things, and performance follows.

For Leaders in Complex Conditions

This distinction matters even more for leaders navigating major change, AI adoption, or organisational restructuring right now. In those conditions, the temptation to grip the performance data harder is understandable. When everything feels uncertain, the numbers feel like the one thing you can see clearly.

But in periods of significant change, the drivers of performance become far more volatile. Clarity is disrupted because the context is shifting. Capability gaps emerge as roles evolve. Energy is depleted because change itself is exhausting. Trust is fragile. Systems are transitional. In those conditions, focusing narrowly on outputs can actively damage the people you need to deliver the change.

The leader who succeeds is the one who keeps asking: what does my team need right now to do this well? What conditions am I creating, or allowing, that are helping or hindering them? That requires genuine curiosity, real listening, and the humility to accept that some of what is driving the performance problem might sit within your own leadership behaviour. That is not a comfortable question, but it is the right one.

One Action This Week

Performance is always produced by a system. Your job as a leader is to understand and actively shape that system, not just hold people accountable for its outputs.

Think of one person or one team whose performance is not where you need it to be. Before any conversation about outputs or standards, spend fifteen minutes honestly mapping the drivers. Do they have clarity? Do they have the capability? Do they have the energy? Is there enough trust? Are the systems working for them or against them?

That fifteen-minute audit, done honestly, will change the quality of every conversation that follows.

The question I want to leave you with: in your leadership right now, are you mostly managing the score, or are you managing the conditions that produce it?

Until next time, keep leading, keep learning, and keep levelling up!

LevelUp

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By Lee Whitmore

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What happens next is predictable. The colleagues who nodded along in the planning meeting suddenly have a clear view, in hindsight, of exactly what was going to go wrong and why it should have been obvious. And the leader, if they’re honest, often starts to believe them.

This is one of the most damaging patterns in leadership. The moment a decision produces a poor outcome, we rush to declare it a poor decision. We work backwards from the wreckage. We reconstruct the story so that the failure feels inevitable, the warning signs feel obvious, and the person who made the call feels foolish.

The problem is that the reconstruction is almost always wrong.

Two Biases You’ve Probably Never Named

Two psychological biases corrupt our evaluation of past decisions in ways we rarely acknowledge and almost never correct for. Understanding them properly is one of the most practically useful things a leader can do.

The first is outcome bias. Research by psychologists Baron and Hershey, dating back to 1988, demonstrated this with elegant simplicity: when the exact same decision was presented to participants, identical reasoning and identical information, they rated it as competent when the outcome was good and poor when the outcome was bad. Most striking of all, when asked beforehand whether outcomes should influence the evaluation of decision quality, the vast majority said no. Everyone agreed on the principle. And then, when the outcome was revealed, they broke their own rule anyway.

The second bias is hindsight bias, the ‘knew-it-all-along’ effect. The research, which goes back to Fischhoff in 1975 and has been replicated extensively ever since, shows that once people know how something turned out, they consistently overestimate how predictable it always was. The event feels retrospectively inevitable in a way it genuinely was not at the time. I go into the research in considerably more depth in the podcast episode, if you want to explore the evidence further.

The two biases work in tandem. Outcome bias says: because the result was bad, the decision must have been bad. Hindsight bias says: the result was always going to be bad, and the decision-maker should have seen it coming. Together, they rewrite history into a story where the failure was foreseeable and the leader was at fault. Neither is usually true. Both feel completely natural.

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The Poker Table and the Supermarket

Annie Duke, former World Series of Poker champion and author of ‘Thinking in Bets’, calls this habit ‘resulting’: judging the quality of a decision purely by how it turned out. In poker, you can make the statistically correct decision with the right odds and the best available information, and still lose the hand. If you then change your strategy based on that single outcome, you’re not learning from experience. You’re abandoning sound reasoning in response to bad luck.wisdomtree+1

It’s a powerful metaphor for leadership. Consider Tesco’s entry into the United States market with ‘Fresh and Easy’. Under CEO Terry Leahy, Tesco was the third-largest retailer in the world. The team spent roughly two years conducting on-the-ground research before a single store opened. The strategic logic was credible: growing American appetite for convenience and fresh food, combined with Tesco’s deep supply chain capability and operational expertise. Fresh and Easy launched in late 2007 and never made a profit. Tesco sold the business in 2013 at a total cost of well over £1 billion.

In the aftermath, the post-mortem was brutal. Commentators identified everything that had gone wrong, and it all felt obvious. But the financial crisis that arrived in 2008, precisely as the new stores were trying to build a customer base, was not a variable that any strategic plan from 2005 could reasonably have accounted for. Was this a bad decision? Or was it a well-reasoned, properly researched strategic call by an outstanding executive, which ran into factors that couldn’t be fully predicted? The degree to which it is now described as obviously doomed is almost entirely a product of hindsight bias. Leahy was not reckless. He was bold, well-prepared, and wrong about some things that turned out to matter enormously. Those are not the same thing.

Now consider the flip side. In 1964, IBM’s president Thomas Watson Junior committed the company to developing the System/360 family of computers at a cost of $5 billion, roughly twice IBM’s total annual revenue at the time. Industry observers called it ‘IBM’s $5 billion gamble’, and not affectionately. The project was chaotic, the engineering challenges enormous. And then it worked: in the first three months after launch, IBM received over $1.2 billion in orders, and the System/360 went on to generate over $100 billion in revenue. Watson is now celebrated as a visionary. But if it had failed, the same decision, made with the same reasoning and the same genuine uncertainty, would have been remembered as reckless overreach. Outcome bias works in both directions. It punishes sound decisions that go wrong, and it canonises bold decisions that happen to go right. Neither verdict is reliable on its own.

What Good Decisions Actually Look Like

If outcomes are an unreliable measure of decision quality, what should we use instead? The honest answer is the quality of the process.

In practical terms, that means asking a specific set of questions at the time of making a decision, and revisiting them honestly in review. Not ‘did it work out?’ but: what information did we have, and was it the best we could reasonably have obtained? Did we actively seek out the case against our preferred option? Did we build genuine challenge into the process, or create an echo chamber? Were we clear-eyed about the uncertainty we were operating in?

The pattern I see most often when working with leaders is that they’ve made reasonable decisions, but they haven’t made the reasoning visible. They haven’t documented the information state at the time. They haven’t created a record of the challenge they built in. And so when something goes wrong, there’s no process to point to, and the narrative fills the vacuum, usually unfairly. Building a transparent, auditable decision-making process protects the integrity of good leadership when outcomes disappoint.

This matters in both directions. A good outcome from a poor process can be more dangerous than a bad outcome from a good one, because it reinforces exactly the wrong habits.

The Single Outcome vs. the Pattern

None of this means bad outcomes don’t matter. Of course they do. The consequences are real, for your organisation and for the people affected. You have to attend to them seriously and with genuine accountability.

But here is the most important distinction: a single bad outcome, even a severe one, is not a reliable verdict on your decision-making process. It may simply mean you made a reasonable call and encountered variables that sat outside any reasonable prediction. That is not a character flaw. It is the reality of operating in a complex world where the range of possible futures is always wider than the one you’re planning for.

A pattern of bad outcomes is a different matter entirely. A consistent pattern of poor results is a signal that deserves rigorous attention, a genuine review of how decisions are actually being made. But the crucial difference is this: a pattern calls for a process review, not a crisis of identity.

If every bad outcome triggers a collapse in your confidence, you’ll eventually stop making the bold, necessary calls that leadership demands. You’ll drift towards timid, consensus-driven decisions designed not to produce the best outcome, but to give you somewhere to hide if things go wrong. The antidote to outcome bias is not paralysis. It is a clear, honest, time-efficient process that you can complete and then stand behind.

For Coaches: What to Listen For

When a client comes to a session carrying the weight of a bad outcome, the first task is to help them separate two questions that often get tangled: was their process sound, and was their outcome good?

Listen for language that tells you they’re doing this. Phrases like ‘I should have known’ or ‘it was obvious in hindsight’ are early markers of hindsight bias in action. Push back gently. Ask them to reconstruct what they actually knew at the time of the decision, not what they know now. Ask them to describe the process they followed: who they consulted, what challenge they built in, what they acknowledged they didn’t know.

The goal is to help them reach a precise, honest verdict. If the process was genuinely flawed, there’s something specific and real to work on. If the process was sound and the outcome was shaped by factors they couldn’t have predicted, help them carry that clearly, so they don’t allow one bad result to become a story about their fundamental capability.

The leaders who handle this best have an almost forensic ability to keep these two conversations separate. They carry their failures without being crushed by them, and their successes with appropriate humility. That kind of grounded confidence is what holds up under pressure.

The question I’d like you to carry from this is a simple one: when you look back at your most recent significant decision, are you evaluating the quality of your process, or are you just counting the score?

Until next time, keep leading, keep learning, and keep levelling up!

LevelUp

Get the weekly briefing that helps you navigate organisational chaos with clarity. From mastering difficult conversations to adopting AI without losing the human touch, LevelUp is your weekly guide to leading with confidence.

By Lee Whitmore

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The 21st of May is Global Accessibility Awareness Day, a date set aside to ask who is being left out by the way we design technology, communication, and working life, and what we lose as a result. It felt like the right moment to write something personal.

The Pattern in Theo’s Story

If you know Theo Paphitis from the television, you’ll recognise the sharp, decisive entrepreneur who always seems to know his own mind. What’s less visible on screen is that Theo has dyslexia, and his path through education was genuinely difficult. He’s spoken openly about being placed in bottom sets, about teachers writing him off, about being told repeatedly that he wasn’t capable.

What those teachers didn’t see was what he was privately building: a relentless ability to problem-solve verbally, to think on his feet, to build understanding through conversation and pattern recognition rather than through text. When he moved into business, that processing style didn’t just survive. It gave him an edge that many conventionally schooled leaders simply don’t have.

Theo now talks about his dyslexia as a superpower, not because the struggle wasn’t real, but because the workarounds he built to navigate that struggle turned out to be some of the most valuable skills he ever developed. The environment created pressure, the pressure created adaptation, and the adaptation created capability. That’s a genuinely important idea, and one that sits very close to home for me.

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Refusing to Hold the Pen

When I was at school, I had absolutely no idea I was processing things differently. I didn’t have a label for it. I just knew that writing felt almost impossible. I’d look at a blank page and something would seize up. Reading was hard too, but it was never reading that really held me back. The inability to put pen to paper was the thing that consistently created anxiety, embarrassment, and the kind of low-level dread that followed me through school and well into my career.

I told myself I was just a bit rubbish at English, that it was a personal failing rather than a different way of processing the world. I carried that quietly for years. It wasn’t until I was well into my thirties that I started to recognise it for what it actually was: not a deficit in intelligence or a reason for shame, but a genuinely different cognitive profile that had been present my whole life.

And once I had that shift in perspective, something else clicked too.

What the Workshops Were Actually Teaching Me

As I climbed through my career, I attended a lot of training sessions, leadership events, and workshops. A familiar format kept appearing: small groups, a task on a flip chart, and the question, ‘Who’s going to take the notes?’ For most people, that’s a logistical question. For me, it was a moment of quiet panic.

So a pattern developed. I noticed that in every group exercise there were two roles: the note-taker and the presenter. I worked out that if I moved fast enough, I could always claim the second one. ‘I’ll present.’ Confident, seemingly enthusiastic, apparently generous. The effect was that someone else always ended up holding the pen.

My motivation at the time was entirely about self-preservation. It wasn’t strategic, and it certainly wasn’t brave. But here’s what happened: by consistently volunteering to present, I started to get good at it. I became comfortable standing in front of a room. I learned how to structure a narrative quickly, how to handle difficult questions, how to read an audience and adapt.

The skills I was building were absolutely intentional, in the sense that I worked hard at them. But the reason I kept putting myself in those positions was, at root, because I was working around a difficulty. The thing I was trying to avoid pushed me directly into the roles that would shape my leadership style.

Now I host a podcast, interview business leaders and authors, speak at events, and coach others on leadership and communication. The thread that runs through all of it goes back to that moment in the workshop where I said, ‘I’ll present’, because I didn’t want anyone to see me writing.

In Enhanced Leadership, I reflect on something similar: ‘Ive always been a listener, a thinker and a talker. I learn best through dialogue and audio, not through reading or lengthy written exercises.’ The irony, of course, is that those same qualities became the foundation of a book, a podcast, and a coaching practice.

What This Means If You Lead a Team

Here’s a challenge worth sitting with. Think about the last time you asked someone on your team to produce a report or present their work as a slide deck. Completely normal requests. But ask yourself this: did you need the report, or did you need the insight? Did you need the slides, or did you need a clear recommendation?

A report is a method. Insight is an outcome. There is an important difference.

When you mandate the method, you are, often without realising it, designing out the people on your team whose thinking doesn’t move in straight lines and dense paragraphs. The person who processes brilliantly through conversation, through diagrams, or through a two-minute verbal brief can meet your outcome perfectly. But they’ll struggle to meet your method. And if you insist on the method, you may never see what they’re actually capable of.

Think of someone on your team who always seems slightly disengaged in written updates but comes alive when talking through a problem. In many cases, the format isn’t revealing their ceiling. The format is the ceiling.

So be brave enough to step back from what feels familiar. If a short voice note captures the thinking just as well as a five-page document, ask for it. Define the outcome clearly, then get out of the way and let your team use the method that works for their brains. AI is already changing this equation: for the first time, people who think brilliantly but have always struggled with written output have a genuine, practical tool to bridge that gap.

For Coaches: What to Listen For

If you coach leaders, be alert to the pattern I’ve described above. Many of the strengths your clients take for granted have their roots in something they once found difficult or embarrassing. The presenting skill, the communication instinct, the ability to think on their feet: often these didn’t come from confidence. They came from compensation.

A useful question to explore is: ‘Where in your career have you consistently volunteered for something? And what were you quietly avoiding at the same time?’ The answer frequently reveals a hidden development path that the client has never fully seen for what it was.

It’s also worth helping leaders examine the formats they demand from their teams. When a leader insists on a particular method of communication, it’s often a reflection of their own preferred style, not necessarily the most effective way to surface good thinking. Coaching them to separate ‘how I like to receive information’ from ‘how insight is best created’ can unlock real change.

The Pressure That Built the Muscle

I spent thirty-odd years thinking my difficulty with writing was something to hide, something that marked me out as less capable. It turned out it was none of those things. It was the pressure that built the muscle, and the muscle that built the career.

Whatever your version of refusing to hold the pen looks like, I’d encourage you to look at it again. Not with shame, and not with forced positivity either, but with genuine curiosity about what it’s been building in you.

And if you lead a team, ask yourself this week: where are you asking for a method, when all you actually need is an outcome? The answer to that question might just change someone’s career.

Until next time, keep leading, keep learning, and keep levelling up!

LevelUp

Get the weekly briefing that helps you navigate organisational chaos with clarity. From mastering difficult conversations to adopting AI without losing the human touch, LevelUp is your weekly guide to leading with confidence.

By Lee Whitmore

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The message is obvious: work smarter, not harder.

I find this image genuinely irritating. Not mildly annoying. Genuinely irritating. And I think it is worth explaining why, because the same flawed logic behind that image is playing out in organisations right now.

What the Story Gets Wrong

The image completely ignores why the blocks are being moved in the first place. These people are not hauling stone for fun. They are building something. A structure that requires precise, flat-faced blocks of specific sizes and shapes, positioned with care and accuracy.

Now look at that round stone ball. What exactly are you going to build with it? You cannot stack spheres into a stable wall. You cannot use them as foundations. That ball is, for the purpose of this project, completely useless.

And here is the part that is rarely mentioned: carving a rectangle into a sphere is not a small job. Someone skilled had to chip away at that block, removing material piece by piece, until they achieved a smooth round shape. That took effort, expertise and time. What were they left with? A pile of stone off-cuts, waste debris that is now lying around getting in everyone’s way, possibly creating extra work for someone else to tidy up.

Let’s take stock of what the so-called smarter person actually achieved. They destroyed a block the project needed. They spent considerable effort creating something that cannot be used. They generated waste. They likely created additional work for someone else. And they moved their stone more easily.

If I were the project leader, I would be furious.

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The Vanity Productivity Problem

Here is what makes this story genuinely dangerous: the ball roller gets the credit. They are the protagonist. The clever one. And that tells you something important about how we sometimes reward behaviour in organisations.

We have a tendency, and I think it is getting worse, to celebrate the visible, quick win over the quiet, unglamorous work of doing things properly. I call it vanity productivity: the pursuit of an outcome that looks like progress, generates attention and approval, but on closer examination either adds no real value or actively damages the wider effort.

The ball roller is the perfect symbol of this. They got to feel clever. They solved their specific, narrow problem with apparent flair. But they ignored the context entirely. They never asked what the stone was for. They did not consider what the project needed. They optimised their own contribution in isolation and left the consequences for everyone else.

I see this pattern regularly. Someone implements a process improvement that reduces their team’s workload but pushes complexity upstream or downstream. Someone launches a shiny initiative that generates internal buzz but was never tested against actual user needs. Someone hits their personal targets in a way that makes the team’s shared targets harder to reach. Each of these people can point to their visible output and say, ‘Look what I did.’ And often they receive the recognition that comes with it.

The problem is that recognition is misaligned with actual value. Over time, that misalignment corrupts the culture.

What Genuine Smarter Working Actually Looks Like

If the ball story is a bad example, what would smarter working actually look like on that project? I think this is worth taking seriously, because the answer is a useful leadership lens.

Real smarter working starts long before anyone lifts a block. It starts with planning. How many blocks do we actually need? Overproduction is an industry: it is waste with good intentions. It continues with sourcing. Is there a closer quarry? The smart choice reduces transport effort before a single rope is picked up. Then there is route planning: identify the obstacles, remove them, level the ground. Preparation that is invisible by the time the block moves, but it is what made the movement efficient.

And then there is the teamwork. The people pulling those ropes are not failing to work smarter. They are combining their individual strength into coordinated collective force. That is sophisticated. It requires communication, timing, trust, and shared effort oriented towards a shared goal. The leader who organises that well, who assigns the right number of people to each block, who ensures nobody is overstretched and nobody is underutilised: that leader is working smarter. They are just not doing it in a way that makes them look individually clever. Which is precisely the point.

Working smarter is often quiet, collective and systematic. It shows up in the outcome, not in the individual’s moment of apparent ingenuity.

What This Means for You as a Leader

If you lead a team, a function or an organisation, I want you to think about whether the culture you have built or inherited is inadvertently rewarding ball rollers. Not because your people are cynical, but because the incentive structures, the recognition patterns, and the way performance is measured can quietly tilt behaviour towards the visible individual win rather than genuine collective value.

The first question to ask is: what do we actually celebrate? Is it the person who solved a problem quickly and noisily, or the person who put in the patient work of preventing the problem from arising in the first place? Prevention almost never generates applause. The fire that did not happen, the conflict managed before it escalated, the careful planning that meant a project ran smoothly: these things are invisible precisely because they worked. And invisible work tends not to get rewarded.

The second question is: how clear are we about what success actually looks like at the project level, not just the individual task level? As I return to repeatedly in my coaching, there is a critical difference between local optimisation and system-level thinking. A leader can hit every individual metric and still damage the overall outcome if those metrics are poorly designed or too narrowly focused. This is why strategy and execution have to be connected. People need to understand not just what they are doing, but why they are doing it and what the broader system needs from them.

The third question is perhaps the hardest: is the culture safe enough for people to raise concerns when a quick win might create bigger problems elsewhere? In a culture where fast, visible results are king, raising a slow, systematic worry takes courage. It requires someone to say, ‘I know this looks good, but I am worried about the downstream effects.’ That person risks being labelled a blocker, a pessimist, a brake on progress. They are frequently the most strategically astute person in the room. Your job as a leader is to make that voice welcome.

A Note for Coaches

If you work with leaders, this is a pattern worth watching for. Look for clients who are proud of activity, but vague about outcomes. Look for clients who frame a recent win in terms of what they did rather than what it delivered for the wider effort. And watch for clients who describe themselves as ‘always firefighting.’ Sometimes that reflects genuine complexity. But sometimes it means the fires are being created upstream by people who are optimising their own patch without considering the system. A good coaching question is simply: ‘Who else is affected by this decision, and do they know about it?’

The Closing Thought

The people pulling the ropes together understood something important. They were part of something bigger than themselves. Their smart working was in service of a shared goal. That kind of intelligence, contextual, collaborative and purposeful, is the kind that builds the thing that lasts.

So here is the question to sit with: is there a ball roller somewhere in your organisation right now? Someone pushing a visible, quick win that looks smart but is costing the project more than it saves? And if there is, what would it take for you as the leader to name it?

If this resonated, you can also listen to the full episode on the Level Up Leadership Podcast, where I go deeper on the story and what genuine smarter working demands of leaders.

Until next time, keep leading, keep learning, and keep levelling up!

LevelUp

Get the weekly briefing that helps you navigate organisational chaos with clarity. From mastering difficult conversations to adopting AI without losing the human touch, LevelUp is your weekly guide to leading with confidence.

By Lee Whitmore

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The question is this: when a team underperforms, what is the first thing we reach for?

Almost always, we reach for the individual. We ask which person needs more training, better feedback, clearer goals. We commission a coaching programme. We restructure someone’s development plan. And sometimes, of course, that is exactly the right call.

But Colin’s work suggests we are systematically missing something more fundamental, and the consequences of that gap are quietly significant.

Structure First, People Second

The central argument of The Collective Edge is that the structure of a team, not the talent within it, is the primary driver of whether that team succeeds or fails. Colin has spent his career researching group dynamics, and his findings are uncomfortable for anyone who has invested heavily in individual leadership development.

He puts it plainly: you can take a group of genuinely talented, capable people and put them into a poorly designed group dynamic, and they will underperform. Conversely, give a group of individually unremarkable performers the right conditions, the right norms and the right dynamic, and they will consistently outperform the superstar team. This is not conjecture. It is backed by decades of research in organisational behaviour.

The four structural forces that determine whether a group thrives are composition, goals, tasks and norms. Who is on the team, what they are collectively trying to achieve, the nature of the work they are asked to do, and the unwritten rules that govern how they interact. When these are well designed, the team has a fighting chance. When they are not, no amount of individual coaching will compensate.

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The Jazz Band Lesson

Colin came to this research through an unusual route. Before his academic career, he was a professional jazz trumpet player. And it was in jazz that he first noticed the phenomenon that would define his research: some groups simply clicked. They played beyond what any individual could have produced alone. Others, despite containing more technically gifted musicians, never found that chemistry.

The jazz band metaphor is not just a stylistic flourish. It is diagnostically useful. The great jazz ensembles in history sit between three and seven members. Basketball teams. Hockey teams. The players who are actually interdependent in a football match at any given moment. Three to seven seems to be the sweet spot in which human beings can genuinely coordinate, listen and adapt in real time.

Now consider what happens in most organisations. A meeting with fifteen or twenty people is unremarkable. Every one of them is nominally expected to contribute meaningfully, and to understand the others well enough to act on shared insight. Colin is blunt on this point: if he had to guess the single most common mistake in the organisations he works with, it would be too many people in the room. Too many people in the meeting, and too many meetings full stop.

The Multi-Team Problem

One of the most resonant parts of our conversation was about the increasing trend of matrix structures and multi-team working. People spread across ten, fifteen, twenty teams simultaneously, never quite sure which role they are playing or what norms apply. It sounds efficient on an organisational chart. In practice, it creates enormous cognitive drag.

Colin draws on the classic research insight around working memory: the rule of seven. We can meaningfully keep track of roughly seven things at a time. That applies not just to the size of a team, but to the number of teams we are juggling. When we push beyond that, coordination loss escalates. People spend increasing amounts of time just reorienting themselves to each team’s context, their role, and the current state of play. The reorientation itself becomes the bottleneck.

His prescription has two tiers. Where possible, reduce the number of teams and keep them small. Where that is not possible, the answer is not to work harder on individual awareness; it is to build system-wide norms, clearer roles and stronger cultures that transcend any single team. The jazz equivalent is the shared musical vocabulary that any two jazz musicians can draw on the moment they play together for the first time. They do not need to start from scratch. The norms are already there.

The Sorting Hat Problem

This leads to one of Colin’s most striking ideas, and the one that has stayed with me the longest. He opens The Collective Edge with a question: is the Sorting Hat the real villain of Harry Potter?

If you know the story, the Sorting Hat places every eleven-year-old entering Hogwarts into one of four houses, based on their defining characteristics. And if you zoom out across the arc of the entire series, both wars in the story map almost perfectly onto house divisions. The school spent years sorting children into fixed categories, seeding intense inter-group competition, and expressing surprise when those same children grew up unable to trust or collaborate across those boundaries.

Colin’s point is not really about fiction. It is about what happens in every organisation when we over-sort people into teams, departments, functions and specialisms, and then inadvertently build reward systems and cultures that pit those groups against each other. We create the conditions for the very conflict and disengagement we spend enormous energy trying to resolve.

The sorting hat metaphor is worth pausing on. Where in your own organisation have you drawn boundaries that now feel permanent? Who is in which box, and what assumptions come with that assignment?

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Healthy Competition, Honestly Examined

Competition within teams deserves its own scrutiny here. There is a powerful motivator in individual competition, and Colin does not dismiss it. When people are genuinely independent and competing against an external benchmark, competition can drive strong performance.

The problem arises when competition is introduced between people who are interdependent. Once that happens, there are two ways to win: perform better yourself, or help someone else perform worse. Over time, research suggests that zero-sum reward structures almost always drift towards the latter. People hoard credit, avoid sharing information, and start paying more attention to attribution than to outcomes.

The healthiest form of competition, in Colin’s view, is against your own past performance. It removes the incentive to undermine others while preserving the motivational tension that drives improvement. As a leader, the practical audit is straightforward: look at your formal reward systems first. If your bonus pool is zero-sum, you are already working against yourself. Then listen for the ratio of ‘I’ to ‘we’ in how your team talks about its work. It is not a precise instrument, but it is a telling one.

What This Means for Leaders

The practical implication of all of this is that leaders need to shift their gaze. Most of the leadership interventions I see are aimed at the individual level, and many of them are genuinely useful. But if the structure of the group is wrong, the intervention lands on sand.

Before you commission the next coaching programme or development day, ask the structural questions. Is this team the right size? Do the members have genuinely diverse perspectives, or have we assembled a group of people who all think similarly because they come from the same background? Are the tasks rich enough to demand real collaboration? Do we have norms that govern how we work together, or are we assuming people will figure it out? Are our reward systems encouraging team behaviour, or quietly punishing it?

The answers to those questions will tell you more about why your team is underperforming than almost any personality profile or individual feedback conversation.

For Coaches

If you work with leaders on team performance, Colin’s framework offers a useful diagnostic lens. When a client presents a team problem, resist the pull towards the individual explanation. Ask them to describe the structure: how many people, what kind of work, what are the actual norms in place, and what does the reward system incentivise? Often, the issue they identify as a person problem turns out to be a design problem.

It is also worth exploring the sorting hat question gently with clients. Where have they, perhaps inadvertently, locked people into fixed categories? Who on their team never gets to play outside their assigned lane? And what would happen if they were given a different context, a different combination of people, a different set of conditions?

The most important shift Colin’s work invites is from treating team performance as a steady state to treating it as a dynamic balance. The tension between cohesion and productive dissent never fully resolves. The leader’s job is to keep watching it, keep adjusting, and resist the temptation to declare the team ‘sorted’.

That last word feels appropriate. The best teams are never fully sorted. They are always in motion.

If this has sparked something for you, I would strongly recommend picking up a copy of Colin’s book, The Collective Edge. You can also find the full conversation on the Level Up Leadership Podcast. And if you find this kind of thinking useful, the themes of trust, accountability and smart team design sit at the heart of everything I write about, including in my book Enhanced Leadership, available at mybook.to/EnhancedLeadership

Until next time, keep leading, keep learning, and keep levelling up!

LevelUp

Get the weekly briefing that helps you navigate organisational chaos with clarity. From mastering difficult conversations to adopting AI without losing the human touch, LevelUp is your weekly guide to leading with confidence.

By Lee Whitmore

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There was a brief pause. A few people probably read it as evasion. But then he leaned in, and what followed was one of the more useful pieces of thinking I’ve heard in a leadership setting for some time. He reframed the question entirely: have you built the right foundations, and are you making consistent, meaningful progress in the right direction? If the answer to both is yes, the timeline will take care of itself. If the answer is no, no timeline will save you.

That moment is worth sitting with.

The Pressure to Look Like You’re Moving

We operate in an environment where visible progress is frequently valued over meaningful progress. Leaders feel the pull to point at milestones, get things launched, and show the board something tangible is happening. That pressure is understandable. But when it starts driving decisions rather than informing them, you begin skipping the slower, less visible work that determines whether any of it actually holds.

The speaker was doing something deliberate: putting the pursuit of outcomes ahead of the pursuit of optics. That takes a certain clarity of purpose, and it reflects a view of strategic leadership that is well worth examining.

One important distinction, though. When I talk about this kind of change, I am referring to large-scale organisational transformation and cultural shift. The kind of work that unfolds over five, ten, sometimes fifteen years. Defined operational programmes, by contrast, absolutely require clear milestones, realistic timelines, and demonstrable progress at every stage. That is just good management. The territory I am exploring here operates on a much longer horizon.

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What ‘Foundations’ Actually Means

The word gets used loosely, so let me be specific. In a leadership context, foundations are not a strategy document or a vision statement on a wall. They are a genuine clarity of purpose: knowing why you are doing what you are doing and being able to connect that to the people around you in a way that actually lands. The human core has to be secure before you build anything on top of it.

When leaders skip this, a recognisable pattern follows. A new initiative launches with energy, resources, and a communications plan. People get trained. Systems get procured. Then, about eight or nine months in, the whole thing quietly loses momentum. Not because the strategy was wrong on paper, but because nobody did the slower, harder work of anchoring it to something real. There was no root system. So when the pressure came, as it always does, things did not hold.

Pace Is Not the Same as Performance

There is a particular anxiety that runs through large-scale change: the anxiety of visible activity. Transformation programmes are expensive and disruptive, and people want to see returns. But when that anxiety starts making decisions on your behalf, you end up rushing implementation, launching phases before they are ready, and jumping to the parts that generate the most visible activity. You skip the unglamorous preparatory work. And almost always, you end up doing that foundational work later, under more pressure, with less goodwill.

In Enhanced Leadership, I describe what I call the ‘bolted-on trap’: the tendency to layer new tools or processes onto existing structures rather than genuinely redesigning from the ground up. The same logic applies to pace. Moving too fast usually means bolting change onto a structure that is not ready for it. The speed feels productive. The results often do not last.

Demanding a fixed end date for cultural transformation is a bit like demanding a fixed date for when your organisation will fully trust new leadership. The conditions have to be right. The work has to be real. Rushing it typically produces a performance of change rather than the thing itself.

What Disciplined Progress Actually Looks Like

I want to be precise here, because this is not an argument for slowness. Purposeful progress and cautious inaction are very different things.

A two-way door is a reversible decision: you can try something, learn, and step back if it does not work. A one-way door locks you into a path that is much harder to undo. Disciplined incremental progress is fundamentally about being honest with yourself about which type of door you are walking through, and applying the appropriate level of scrutiny to each.

Under pressure to show momentum, leaders tend to lose that distinction. Everything starts to feel like it needs to happen at the same speed. People stop tracking which decisions are reversible and which are not. Before long, you have walked through several one-way doors without adequate thought, simply because the pace of the programme swept you past them.

The leaders I have seen do this well share a particular quality. They are comfortable with ambiguity in the timeline. They can hold ‘I don’t know exactly how long this will take’ without it undermining their clarity about direction. They know where they are going. They know the next right step. And they trust that doing each step well matters more than doing all the steps quickly.

The AI Dimension

The pace problem is felt most acutely right now in the AI and digital space. No sooner have you started implementing one solution than something better arrives. That is not a temporary condition; it is the landscape for the foreseeable future.

So how do you lead a long-term transformation in a structurally and persistently unstable environment? The answer, I think, is that you decouple your strategy from any specific tool. Your direction of travel, your ‘why’, your long-term outcomes: those need to be durable. They need to survive the next release cycle, the next platform, the next vendor update. The cultural capability you are building in your people, the trust between you and your team, the ethical guardrails you have put in place: none of that becomes obsolete because a new model dropped on a Tuesday.

What should change is your route. This is where governance earns its keep. Too often it becomes a scrutiny exercise dressed up as rigour. But governance at its best holds the long-term outcome steady while giving you permission to adapt the how. It stops you chasing every new development and losing sight of what you were actually trying to build.

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For Coaches: What to Watch For

If you are coaching a leader through a major transformation, watch for the moment when timeline pressure starts to compress their thinking. The questions worth asking are not ‘are you on schedule?’ but ‘do you still know why you are doing this?’ and ‘are the decisions you are making this week reversible?’

Watch also for the ‘bolted-on’ signal: when a leader describes adding new capability to an existing structure rather than redesigning from the ground up. It usually means the foundations have not been properly examined. That is the conversation to have, even when there is pressure to press ahead.

The Question Worth Sitting With

So when someone asks how long your transformation will take, the honest answer might genuinely be: I do not know exactly. But I know the direction. I know the foundations we are building. And I know the next right step. For long-term cultural and organisational change, that is not a gap in your strategy. That is your strategy.

The question I would leave you with: where are you currently measuring pace when you should be measuring direction?

Until next time, keep leading, keep learning, and keep levelling up!

LevelUp

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By Lee Whitmore

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That’s a bold claim. In my experience, it’s also entirely accurate.

https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/courageous-conversations-how-to-lead-with-heart

The Context Behind the Research

The research backdrop deserves attention before we get into the substance. Fifty-three percent of senior leaders currently report feeling burned out. Eighty-four percent feel underprepared for the disruptions ahead. Most telling of all: 75 percent of employees say their boss is the most stressful part of their working day, and only 25 percent believe their leadership culture genuinely inspires them.

Read those figures carefully. Leaders are struggling, and the people watching them are struggling as a result. Yet the default response in many organisations is another strategy deck, another offsite, another values workshop. The McKinsey article makes a clean and important argument: the answer isn’t more collateral; it’s more courage.

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Four Patterns, One Thread

The article builds its argument around four recurring patterns of courageous conversation: legitimising professional dissent; clearing ‘withholds’ with transparency; bringing performance truths to every interaction; and shaping a performance culture with honest feedback. Each is distinct. Together, they form something more coherent than a framework. They form a philosophy of what it means to lead with integrity at every level of an organisation.

What unites all four is a principle worth naming clearly before examining each one: the gap between what a leader says they value and how they behave in unscripted moments is where culture is actually set. A leader’s tone in those moments sets the cultural norm more than any slide deck. That line appears almost as an aside in the article, but it carries weight. It connects directly to what I explore in Enhanced Leadership: that authenticity is the alignment between what you believe, what you say, and what you do. When those three diverge, people notice, and they adjust their behaviour accordingly.

Dissent as a Duty

The first pattern is perhaps the most structurally important. Teams with high psychological safety are two to three times more likely to generate breakthrough ideas, yet dissent is routinely suppressed through hierarchy, inertia, or fear of reprisal. McKinsey’s data is striking: transformations are 5.3 times more likely to succeed when leaders role-model the behavioural change they are asking for.

The article’s framing of this is precise. Dissent is positioned not as defiance but as duty; an obligation built into how the team operates. One CEO opens every executive meeting with: ‘What are we not seeing? What are we not saying?’ That single, repeated habit shifts a culture from guarded compliance to genuine contribution. The structural tools support this: premortems to surface blind spots before decisions are made, a rotating ‘chief challenger’ role in meetings, and deliberate tracking of where challenge comes from across levels and functions. These mechanisms normalise dissent before it feels necessary, so that when something genuinely important needs to be said, the infrastructure is already there.

Withholds: The Silent Drag on Performance

The second pattern is the one most leaders avoid naming. Withholds are unaired truths: resentments, broken agreements, disappointments, and even withheld appreciation that quietly corrode trust over time. McKinsey’s data on this is stark. Unresolved tensions can reduce collaborative performance by 30 percent, while teams with high relational trust outperform peers by 50 percent over time.

The article draws on a Robert Frost line here: ‘Something we were withholding made us weak / Until we found out that it was ourselves.’ The courage required to clear a withhold is not theatrical; it’s intimate. It requires a leader to name what has frayed, repair it without blame, and move forward. A healthcare example in the article illustrates the proportionality of what’s possible: a leader prompts two colleagues showing friction to have a real conversation. Three minutes to clear the air; 57 minutes of measurably better collaboration. That’s not a culture programme. That’s a human instinct, acted on. The discipline lies in creating the conditions where it happens routinely rather than only in crisis.

Performance Truths: Hardware and Software

The third pattern is where I think McKinsey offers some of its sharpest thinking. The article introduces a distinction between hardware and software in performance conversations. Hardware is the objective layer: facts, KPIs, timelines, decision criteria, and resource constraints. Software is the human layer: tone, timing, intention, and relational context.

This distinction matters because most difficult performance conversations fail not for lack of facts but for failure of delivery. A leader who separates ‘the standard is X’ from ‘here’s why it matters and how I want to help you get there’ creates a conversation that is both clear and humane. One without the other either confuses or wounds. The practical reframe here is powerful: clarity is a kindness, and ambiguity is a burden. Giving someone a clear picture of what success looks like is an act of respect, not aggression.

Fewer than one in three employees believe their performance reviews actually help them improve. That’s not because performance reviews are inherently broken. It’s because most of them blur the hardware and software in ways that feel more like judgment than guidance.

Honest Feedback: Looking Forward, Not Just Back

The fourth pattern is the one most leaders believe they already do well, and usually don’t. The problem with feedback in most organisations isn’t that people dislike it. They dislike feedback that is vague, delayed, and framed as judgment rather than development.

The concept I find most useful in this section is the distinction between feedback and ‘feedforward’: focusing on who someone can become, not just what they did. This is a subtle but significant shift. Feedback looks backward. Feedforward is oriented towards growth. The best leaders do both: they name what happened clearly, and they point towards what’s possible. Done well, this becomes a moment of recognition. The article captures the aspiration simply: the aim is for someone to feel ‘She sees me’ or ‘He understands what I’m capable of.’

The practical examples span sport, the arts, and business. A theatre director’s precise note: ‘Pause half a beat before that line.’ An energy CEO sending personal voice notes to her top 50 leaders and explicitly inviting feedback on herself. Military hot washes immediately following missions. The pattern across all of them is rhythm. Feedback given constantly becomes noise. Given regularly, specifically, and with genuine care, it becomes fuel.

The Seasons of Leadership

One dimension of the McKinsey article that deserves more attention than it typically receives is the seasonal model drawn from their book A CEO for All Seasons. The article describes how each phase of a leader’s tenure calls for a different expression of courage: transparency about what you don’t yet know in the early stages; honest standards and feedback as you build; naming complacency and challenging entrenched thinking when the organisation needs renewal; and, finally, handing over power with grace and speaking truth to legacy.

This is a quietly important insight. Courage is not a fixed posture; it’s a contextual discipline. The courage required in your first 90 days is different from the courage required when you are the established authority who needs to disrupt their own thinking. Leaders who understand this have a much richer model for developing themselves across a career, rather than assuming that the habits that served one season will serve all seasons.

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What This Means in Practice

McKinsey closes with a deliberately modest weekly challenge: ask for one dissenting view, request one piece of feedback, or clear one lingering tension. Most leaders will find that one or two of those three feel genuinely uncomfortable. That discomfort is the useful signal: it points directly to where the work is.

The deeper message of the article is that courageous conversations are not exceptional events reserved for crisis moments. They are the ordinary texture of excellent leadership: meetings opened with genuine questions, tensions named before they calcify, performance discussed with clarity and humanity, and feedback given as an act of care rather than obligation.

Your tone in those moments matters. But the broader ask is more demanding than tone alone. It’s about the consistent, deliberate practice of choosing courage over comfort across all four of these dimensions, every week, in every season of your leadership.

That’s what the article is really asking of us.

For Coaches

What to notice: Clients often arrive having conflated busyness with bravery. They’re working hard, running fast, and still avoiding the one conversation that would change everything. Listen for patterns of deferral: ‘It’s not the right time yet’, ‘I don’t want to derail them just before the deadline’, ‘They probably already know’. These are signals, not reasons.

Questions that help: ‘Tell me about the last time you withheld something from a direct report or a peer. What were you protecting, them or yourself?’ Then slow down and examine the gap between what the client claims to value, candour, trust, direct feedback, and how they describe reacting when someone challenges them in the moment. That gap is where the coaching lives.

The seasonal frame: Ask leaders where they are in their tenure. The courage required at six months is different from the courage required at six years. Help them articulate what courageous leadership looks like in their specific season, not in the abstract. Specificity is everything here.

If this landed with you, the full podcast episode exploring these themes is available here:

And if you want to go deeper on the human foundation underneath all of this, my book Enhanced Leadership is available at mybook.to/EnhancedLeadership.

Until next time, keep leading, keep learning, and keep levelling up!

LevelUp

Get the weekly briefing that helps you navigate organisational chaos with clarity. From mastering difficult conversations to adopting AI without losing the human touch, LevelUp is your weekly guide to leading with confidence.

By Lee Whitmore

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That gap, between what leaders believe and what they actually do, was at the heart of a recent conversation I had with executive coach and advisor Chris March on the Level Up Leadership podcast. Chris works with founders and leadership teams across Australia and the US, and he sees this pattern constantly. The people who built something from scratch, who drove success through sheer personal bandwidth, often find it hardest to let go. Not because they are control freaks. Because they care deeply.

But caring deeply is not the same as leading effectively. And at some point, the two come into conflict.

The Bottleneck Problem

The higher you sit in an organisation, the more your instinct is to stay close to every significant decision. That instinct made sense when you were closer to the front line. It made sense when the organisation was smaller and your judgement was the fastest path to the right answer. But organisations grow, complexity increases, and the same instinct that served you well then starts to create drag.

Chris described it simply: if every decision has to travel up to you before anything can move, you have not built a business, you have built a dependency. Every delay carries a cost. Engineers pause mid-project. Sales teams lose momentum. Market opportunities close. That cost rarely shows up neatly on a balance sheet, but it compounds quietly and consistently.

In Enhanced Leadership, I ask leaders to sit honestly with the question: am I focused on doing the work, or enabling the work? The two feel similar from the inside, but they produce very different organisations. Doing the work feels productive. Enabling the work is what actually scales.

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Three Triggers Worth Knowing

So how do you build a structure that allows people to move with confidence while still ensuring you are informed when it matters? Chris offered one of the clearest frameworks I have heard: give people the autonomy to make decisions, but define three specific triggers that require escalation. Is there a financial impact? Is there a customer impact? Is there a people impact? If none of those three apply, the decision belongs to the person closest to it. If one of them applies, that is when the next layer up needs to be involved.

That clarity does something important. It removes ambiguity, which is one of the main reasons people escalate unnecessarily. If your team do not know where the line is, they will always err on the side of caution and bring decisions upwards. You end up overwhelmed not because people are incapable, but because no one told them what they were allowed to decide.

Alongside this, Chris emphasised the importance of delegating with genuine precision. Stating an outcome and a timeline. Thirty days. An email update. A clear definition of what done looks like. Without that specificity, two leaders can delegate in completely different ways, and their teams end up confused rather than empowered.

The One-Way Door Test

Not every decision deserves the same speed of thinking. Jeff Bezos popularised the idea of one-way doors and two-way doors, and it remains one of the most useful mental models I know. A two-way door is a decision you can walk back from if it goes wrong. A one-way door locks behind you.

For two-way door decisions, speed and autonomy are exactly right. The cost of a small mistake is a learning experience, not a catastrophe. On my very first podcast episode, I told the story of a manager who would not spend a few pounds replacing some light bulbs without waiting for approval. That is a two-way door with the handle practically falling off. The whole point of pushing decision-making down the organisation is to move quickly on exactly those kinds of calls.

One-way doors are different. When the stakes are high and the decision is hard to reverse, that is precisely when you slow down, bring in diverse perspectives and apply real deliberation. The mistake many leaders make is applying one-way-door caution to every decision they face. That is how procrastination disguises itself as rigour.

The Sanitisation Effect

One of the more uncomfortable truths Chris and I discussed is what happens to information as it travels upward through an organisation. By the time a message reaches the top, it has usually been cleaned up. Softened. Tidied. Not out of dishonesty, but because people present their best case. They want to reassure. They do not want to alarm unnecessarily. And so the senior leader ends up with a clear and positive picture that may not reflect reality on the ground.

This is why mechanisms that cut through the layers matter. Reverse mentoring, where an executive regularly sits down with someone much more junior, can surface the honest version of what is happening far more effectively than a quarterly survey. An open brief, like the example I shared of a leader who asked her middle managers to come and tell her what they thought mattered most, with no pro forma and no agenda, builds the kind of trust where people will actually tell you the truth.

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For Coaches: What to Watch For

If you work with leaders on delegation and decision-making, the presenting issue is rarely the real one. Clients often come describing a structural problem, when the underlying issue is about identity. Their sense of self-worth is tightly bound to being the person who decides. Letting go feels like losing status, or losing control, or trusting in people who might not yet have proven themselves.

The question worth sitting with is not how do I delegate better? It is what am I actually afraid will happen if I do? That is usually where the real work begins.

Chris also made a point that cuts across cultures and geographies: everyone wants to be seen, heard, and valued. Before any strategy or framework lands, the human relationship has to be there. The leader who knows why each person turns up to work every day, what they care about and what they are trying to build, will always have more genuine buy-in than the one who relies on the authority of the org chart alone.

In a world increasingly shaped by AI, that human thread is not a nice-to-have. As Chris put it: AI is there to amplify your brilliance. The human connection is the edge that no algorithm can replicate.

If this resonated, you can explore more on decision-making, leadership under pressure, and you want to go deeper on leading with purpose in an AI-driven world, my book Enhanced Leadership is available at mybook.to/EnhancedLeadership.

If you want to connect with Chris you can find him on linkedin.com/in/christopherrmarch/ or at chrismarchcoaching.com

Until next time, keep leading, keep learning, and keep levelling up!

LevelUp

Get the weekly briefing that helps you navigate organisational chaos with clarity. From mastering difficult conversations to adopting AI without losing the human touch, LevelUp is your weekly guide to leading with confidence.

By Lee Whitmore

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To find out, I decided to run an anonymous pulse survey on LinkedIn. I wanted to see if the reality on the ground matched the official corporate narrative, or if we were looking at a massive hidden shift in how work gets done.

I have touched on these themes before in my previous guest article, The Shadow AI Economy, where I explored the hidden financial and operational implications of unsanctioned tech. This new data, however, brings the human element into even sharper focus.

As I explore in my book, Enhanced Leadership, true progress often happens in the quiet spaces where traditional management has not yet reached. We are currently witnessing a grassroots transformation that is both thrilling and, for some, a little bit daunting.

The Core Concepts of the AI Shift

To understand this phenomenon, we must look at three primary frameworks: the Governance Gap, the Transactional Mindset, and the transition from Control to Stewardship.

The Governance Gap represents the distance between employee adoption of new technology and the official policies of the organisation. When this gap grows too wide, ‘Shadow AI’ emerges. This refers to the use of unsanctioned tools to complete professional tasks.

The Transactional Mindset describes how employees prioritise immediate efficiency over abstract corporate risk. Finally, moving from Control to Stewardship involves leaders stopping the attempts to block usage and instead guiding their teams toward safe, ethical, and productive habits.

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A Deep Dive into the Internal Data

I chose an anonymous pulse survey format because it is the most effective way to get honest answers about sensitive topics like unsanctioned software use. I kept it brief, asking only a handful of targeted questions to minimise the time burden on respondents while ensuring their identities remained completely protected. By using a secure link that did not require a sign-in, I was able to gather candid feedback from 43 professionals across different sectors.

The results were eye-opening. The first thing that jumps out is the adoption rate; a staggering 90.7% of respondents said they are currently using AI tools in their roles. However, the gap between usage and governance is where the real story lies. While nearly everyone is using it, only 12.8% of those users could say for certain that the tools they were using were officially approved by their organisation.

The vast majority, around 70%, were not sure if their tools were sanctioned at all. Even more telling was the attitude toward that lack of approval. When asked if they cared whether the tools were officially approved, 59% of users simply said they did not care. In Enhanced Leadership, I write: ‘Leadership is not about the enforcement of rules for their own sake, but about creating an environment where the right path is also the most accessible path.’ Currently, the ‘right’ path for many employees is the one that allows them to finish their work by 5:00 PM, regardless of the software source.

The Global Context and Economic Impact

If you are a leader listening to this and feeling a bit of a cold sweat, you should know that my survey is not an outlier. It is a microcosm of a global shift. The 2024 Microsoft and LinkedIn Work Trend Index found that 78% of AI users are bringing their own tools to work. Their research suggests that employees are often reluctant to admit they use AI for their most important tasks because they fear it makes them appear replaceable.

In the UK specifically, a Microsoft study from late 2025 found that 71% of employees have used unapproved consumer AI tools at work. These workers are saving an average of nearly eight hours a week. To put a number on that, Microsoft estimates this contributes roughly £208 billion in value to the UK economy. This is a massive injection of productivity that is currently unmanaged and unmeasured.

However, there are significant risks to consider. Gartner, the global research and advisory firm, provides data-driven insights to senior business and technology leaders. Their research shows that 69% of organisations already have evidence of employees using prohibited public AI tools. They predict that by 2030, 40% of companies will suffer security or compliance incidents directly linked to this unauthorised usage. We are currently in a crisis of governance where the pace of employee adoption is simply outstripping the pace of leadership.

Practical Advice for Leaders

As leaders, we have a clear corporate responsibility. We are bound to ensure our staff are compliant with data laws and security protocols. We cannot simply look the other way while sensitive company data is fed into public models. If your staff are using unapproved tools, it is usually because you have a gap in your own provisions. They are responding to pressure for speed and quality.

My first piece of advice is to audit the gap. Instead of looking for people to catch, look for the ‘why’. If your team is using an unapproved AI to summarise meetings, it means your current software is failing them. Engage with them rather than indicting them. Start an open dialogue. Ask your team what tools are making their lives easier right now. You need to know what they are using so you can help them use those tools safely.

Next, you should shift the conversation from ‘no’ to ‘how’. Move away from telling people they are not allowed to use these tools and start showing them how to use them responsibly. This means setting clear acceptable use policies and providing approved tools that have privacy built-in. You might consider looking at frameworks like ISO 42001, which helps organisations establish a managed system for AI that emphasises ethical and responsible use.

Finally, create a safe sandbox for experimentation. Provide a list of vetted tools that satisfy corporate security but still offer the flexibility staff need. Treat shadow AI as a systems problem, not a discipline problem. When you provide a secure alternative that is just as easy to use as the public one, the risk of shadow usage drops significantly.

Practical Advice for Coaches

For those in the coaching profession, these findings offer a unique opportunity to support clients through a period of intense technological anxiety. Coaches should focus on the human element of the AI transition. Many employees use these tools in secret because they fear obsolescence. Your role is to help them see AI as an augmentative partner rather than a replacement.

Encourage your clients to be transparent with their leadership about the efficiencies they are finding. Help them frame these discoveries as ‘innovation pilots’ rather than policy violations. By coaching individuals to lead from the middle, you help bridge the gap between the executive suite and the front line. As I mention in Enhanced Leadership, ‘The coach’s primary duty is to shine a light on the shadows, making the invisible visible so that it can be managed with intention.’

Leading the Revolution

True leadership in the AI age is about stewardship. It is about creating a culture where innovation and responsibility live side by side. The AI revolution is here. It is not waiting for your next board meeting. It is happening right now, one prompt at a time.

I encourage you to take this data back to your teams. Use it as a conversation starter. If we can move past the fear of Shadow AI, we can unlock a level of productivity and creativity that was previously unimaginable. The question is: are you going to lead it, or just watch it happen from the sidelines?

To dive deeper into these concepts, I invite you to listen to my latest podcast episode where we break down these survey results in even more detail.

Until next time, keep leading, keep learning, and keep levelling up!

LevelUp

Get the weekly briefing that helps you navigate organisational chaos with clarity. From mastering difficult conversations to adopting AI without losing the human touch, LevelUp is your weekly guide to leading with confidence.

By Lee Whitmore

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So I did something about it. I put in some hard yards doing proper research. That process started, somewhat inevitably, with AI-assisted research tools, but I was deliberate about how I used them. I specifically prompted for breadth rather than confirmation, asked for counter-views, and made a point of verifying sources against peer-reviewed articles and credible institutional reports. I then loaded the material into Google NotebookLM to build a structured foundation before going deeper. And go deeper I did: several full articles read in their entirety, hours of substantive content consumed. I had not planned to go that far. But each layer I peeled away made me more concerned, and that concern made it feel more important to get this right. Intellectual honesty has a momentum of its own once you let it start moving.

The moment that crystallised everything came from an unexpected direction. I had asked NotebookLM to produce an audio summary of the research, specifically framed for “presenting at a team meeting”, something accessible that would help a non-specialist audience engage with the material without being overwhelmed. The summary did its job. It covered the key findings clearly and progressively. But as it moved toward its conclusion, the tone shifted. The predictions about exponential growth in power and water consumption, if current trajectories continue unchecked, became increasingly stark. And then, at the very end, the AI-generated voice wrapped up with what could only be described as a sarcastic sign-off: ‘Good luck at your next team meeting.’

I laughed. And then I sat with it for a while. Because buried in that throwaway line was something pointed. The research, synthesised and reflected back through an AI tool, had essentially arrived at the same place I had: the scale of what is coming is genuinely difficult to communicate in a setting designed for forty-five-minute agendas and action points. The gap between the evidence and the average organisational conversation about AI is significant.

This article is my attempt to help close that gap, with honesty about the challenges and equal honesty about the reasons for genuine, evidence-based optimism.

I want to be clear about my own position going into this. I am not an AI sceptic. I use these tools daily, I help leaders think through how to adopt them, and I believe the productivity and creative potential they unlock is real. But I am increasingly convinced that enthusiasm without literacy is a liability, and that the most valuable thing I can do, both in my coaching work and in writing like this, is model what it looks like to engage with AI seriously rather than selectively.

What the Evidence Actually Shows

The Ethical Dimension

The most persistent myth in AI adoption is that these systems are neutral because they are mathematical. The reality, documented across sources including the USC Annenberg analysis of AI’s ethical dilemmas, comparative framework research across IEEE, EU, and OECD guidelines, and the Stanford HAI AI Index Report, is that AI systems inherit the biases of their training data, and that data reflects the inequalities of the world that produced it.

The consequences are not theoretical. In hiring, AI screening tools have systematically disadvantaged applications from women in technical roles. In lending, algorithmic credit-scoring has consistently produced worse outcomes for applicants from minority communities. In facial recognition, error rates for darker-skinned individuals run dramatically higher than for lighter-skinned ones, a disparity with serious implications when such systems inform identification decisions. These are documented patterns across multiple sectors and geographies, not edge cases.

This matters to me personally, not just academically. One of the core arguments I make in my work is that leadership is fundamentally about how power is exercised and who it serves. When we uncritically adopt AI systems that replicate and scale existing power imbalances, we are not being neutral. We are making a choice, and we should own that choice rather than hiding behind the word ‘technology’.

Alongside bias sits the problem of transparency. The most capable AI models tend to be the least interpretable. They produce outputs through processes that even their creators cannot fully explain, which creates a fundamental accountability problem when those outputs shape consequential decisions about health, finance, employment, or legal status. The EU’s AI Act and IEEE’s ethical framework both identify explicability as a core requirement for trustworthy AI, yet the tension between interpretability and performance remains live. Organisations are making real decisions in that gap, often without acknowledging that the gap exists.

Privacy sits at the third corner of this ethical triangle. AI’s requirement for data at scale means that personalisation and surveillance are, architecturally, very similar things. The Stanford HAI report notes that as AI capabilities expand, so does the surface area for manipulation and profiling, and that the individuals most affected are typically those with the least power to resist it. The T20 India policy brief on environmental and ethical AI challenges flags accountability as a governance gap of genuine urgency, arguing that liability frameworks need extending to cover AI-mediated harms with the same rigour applied to any other product or service.

What runs through all of these concerns is a structural observation drawn from the broader AI ethics scholarship: bias in AI is not a technical bug waiting for a patch. It is a structural problem rooted in who builds these systems, whose data is used, and whose interests are centred in the design process. Fixing it requires institutional change, not just algorithmic adjustment. That is harder, slower, and less comfortable than a software update. It is also the only approach that will actually work.

There is, however, real progress to note. The AIHub review of top AI ethics and policy issues from 2025 reports that AI safety infrastructure experienced rapid and meaningful growth last year. Safety, once discussed primarily in conceptual terms, has evolved into a structured engineering discipline, with independent third-party auditing processes and evaluation centres emerging as a genuine checks-and-balances layer. Leading AI laboratories including OpenAI, Google, Anthropic, and Alibaba adopted standardised benchmarks for assessing deception, persuasion, and planning. The UK proposed its AI Growth Lab, a sandbox for testing new models under real-world conditions. These are meaningful structural improvements, and they matter.

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The Environmental Dimension

If the ethical landscape is complicated, the environmental picture is in some respects more concrete, and as a result more difficult to sit with comfortably. The research is increasingly robust, even if the data disclosed voluntarily by AI companies remains frustratingly incomplete.

Training a single large AI model can emit hundreds of metric tons of CO2. The Cornell University roadmap on the environmental impact of AI data centres, published in late 2025, projects annual carbon emissions from AI infrastructure reaching 24 to 44 million metric tons by 2030. The Oeko Institut’s detailed study adds important nuance: inference, the ongoing act of running deployed models to generate outputs, now accounts for 80 to 90 per cent of AI’s operational energy use. Training happens once. Inference happens billions of times daily. The energy cost does not front-load and then plateau; it scales continuously with adoption.

Water consumption compounds this picture. Data centres require enormous volumes of water for cooling, and the siting of large AI infrastructure in regions already experiencing water stress creates compounding scarcity problems. The International Science Council’s report and the ArXiv paper on AI’s ecological impact both highlight that the hardware running these systems has a short operational lifespan relative to its manufacturing and materials cost, generating an e-waste problem that is rarely factored into AI’s environmental accounting.

The civil society report from February 2026 challenges one of the most commonly used rhetorical escape hatches for AI companies facing environmental scrutiny: the argument that AI’s footprint is justified, or offset, by its potential to help solve the climate crisis. This is not an entirely false argument. The LSE Grantham Institute’s study found that AI applied at scale in energy and transport could reduce global emissions by 3.2 to 5.4 billion tonnes annually, a figure large enough to take seriously. But potential future benefits do not cancel out present costs, and the civil society report is right to insist on that distinction.

The Journal of Environmental Management’s global assessment ‘The Two Tales of AI’ frames the duality well: in one scenario AI accelerates decarbonisation; in the other, efficiency gains are rapidly consumed by scale and rebound effects. Which story becomes dominant is not determined by the technology. It is determined by choices. That framing resonates with me strongly. In my work with leaders navigating major change programmes, the pattern is consistent: the technology rarely determines the outcome. The decisions made around the technology do.

The Counterbalance: Where Genuine Progress Is Happening

It would be intellectually dishonest to present only the challenges without acknowledging the genuine, evidence-based reasons for optimism, and there are several that deserve serious attention.

Efficiency gains in AI systems have been extraordinary. Nvidia’s research published in late 2025 found that energy efficiency in large language model inference has improved by a factor of 100,000 over the past ten years. That is not a marginal improvement. It means that the AI capabilities available today cost a fraction of what equivalent capabilities would have consumed a decade ago, and the trajectory continues. If this efficiency curve persists, the absolute energy cost of AI’s growth may be significantly lower than projections based on historical consumption patterns suggest.

The energy transition itself is being accelerated, in part, by AI’s own appetite. Renewables accounted for over 90 per cent of new utility-scale generating capacity in 2024, partly because they are faster to deploy and easier to scale, and the pressure from data centre demand is pushing utilities and investors to accelerate clean energy development. AI is already demonstrating real value in grid management: within power networks, AI improves forecasting and fault detection, reducing outages by 30 to 50 per cent and enabling better integration of renewable energy sources. AI-managed lighting, heating, and cooling in buildings could save 300 TWh annually, equivalent to the total electricity usage of Australia and New Zealand combined.

The Cornell roadmap, for all its sobering projections, also identifies a practical path forward: deploying advanced liquid cooling and improved server utilisation could reduce carbon emissions by a further 7 per cent and lower water use by up to 32 per cent at existing data centres. That is achievable with currently available technology and deliberate infrastructure investment, not a distant aspiration.

A study published in March 2026 found that while AI consumes electricity at the scale of a country like Iceland, its overall contribution to global emissions may be far smaller than the headline figures suggest, and that the more localised impacts around specific data centres are the more pressing and tractable concern. That reframing matters: it points the conversation toward targeted, solvable problems rather than undifferentiated alarm.

I find this genuinely encouraging, and not in a naive way. I have been in enough strategic change programmes to know that the problems that kill organisations are rarely the ones nobody saw coming. They are the ones people saw coming but felt too big to address incrementally. AI’s environmental and ethical challenges are large, but they have identifiable entry points, measurable indicators, and growing bodies of practice around mitigation. That is a different kind of problem from an intractable one.

Three Layers of Responsibility

The research points consistently to the same conclusion: the risks are real, the trajectory is not fixed, and the outcomes depend on choices made at multiple levels simultaneously. What follows is not a set of abstract principles but a practical framework, organised by where the levers actually sit.

Layer One: Global AI Infrastructure

The first layer sets the conditions within which everything else operates. AI infrastructure, meaning data centres, energy grids, chip supply chains, and training pipelines, is concentrated in relatively few hands and governed by a patchwork of national and voluntary frameworks that does not match the global scale of the technology.

The regulatory picture is uneven in ways that matter. The EU’s AI Act is the most comprehensive legislative attempt yet to codify requirements around transparency, accountability, and risk management. But regulation is jurisdictionally bounded and AI is not. Without binding international frameworks, countries that establish robust ethical standards risk simply displacing irresponsible AI development to jurisdictions with fewer constraints, rather than raising the global floor. Progress on multilateral coordination has been slow, and that slowness is itself a policy choice with consequences.

The Cornell roadmap and the Oeko Institut research both identify mandatory disclosure of energy and water consumption figures from AI operators as a high-leverage intervention, applying transparency standards already common in other high-impact sectors. Carbon pricing mechanisms that account for AI infrastructure’s footprint, alongside renewable energy procurement requirements that go beyond matching to actual clean operation, are identified across multiple reports as necessary systemic interventions. The OECD’s methodological work on measuring environmental impacts creates the foundation for this; what is lacking is regulatory will to make it compulsory.

The optimistic read at this level is that the direction of travel in several major jurisdictions is broadly correct. The UK’s AI Growth Lab, the EU’s enforcement of the AI Act, and the emergence of independent auditing infrastructure all represent structural improvements that were not in place five years ago. The policy scaffolding is being built. The question is whether it is being built quickly enough.

Layer Two: Organisational Decisions and Deployment

This is where most leaders reading this will find their most direct leverage. Organisations adopting AI are not passive recipients of the technology’s consequences. They are active participants in shaping them. The choices made about which tools to deploy, for what purposes, with what governance structures, and with what accountability to those affected, are consequential choices that aggregate into the overall picture.

The ethical frameworks reviewed across this research, whether IEEE, EU, or OECD, converge on a set of principles that translate directly into practice. Transparency means communicating clearly when AI systems are being used and how they affect decisions. Accountability means establishing clear lines of responsibility for AI-mediated outcomes and ensuring redress mechanisms exist when those outcomes cause harm. Proportionality means matching the capability and opacity of an AI system to the stakes of its application. Human oversight means maintaining genuine human judgement in high-stakes decisions rather than treating AI outputs as final.

I speak to leaders across a range of industries, and the pattern I see most consistently is not malicious intent. It is governance that lags behind adoption. Organisations move fast to implement AI tools because the competitive pressure to do so is real, and the ethical and environmental review structures simply have not kept pace. That is a fixable problem, and the organisations that fix it early build something genuinely durable: the credibility that comes from being able to demonstrate that their AI use is both effective and accountable.

Build ethical review into early stages of AI procurement and development cycles, not as an afterthought audit at the point of deployment. The Stanford HAI report and the USC Annenberg analysis both note that organisations embedding ethical review early produce materially better outcomes than those treating it as a compliance checkbox completed after the fact.

Ask AI vendors directly for energy and water consumption data for the services being purchased. This data exists. Many vendors simply do not publish it unless asked. Factoring it into procurement decisions applies the same supply chain responsibility that organisations increasingly apply to other resource categories.

Include AI energy consumption in existing carbon accounting and sustainability reporting frameworks. This is methodologically feasible today, using the OECD’s measurement guidance as a basis, and it closes the gap between an organisation’s stated sustainability commitments and its actual AI-related footprint.

Invest in AI literacy across leadership teams, not just technical fluency but genuine critical capacity: understanding failure modes, limitations, and the structural contexts in which these systems operate. The AIHub ethics review identifies institutional literacy as increasingly central to ethical deployment, and the responsibility to build it sits with organisations, not individual users.

Smaller, purpose-built models for specific organisational tasks use a fraction of the energy of large generalised systems. Where the use case allows it, choosing the efficient tool rather than the most impressive one is a meaningful and immediately actionable environmental decision.

Layer Three: Individual Personal Responsibility

The third layer is the one most easily underestimated, and it is where this article’s personal opening becomes most relevant. The individual choices made by professionals engaging with AI, about how they use it, how they talk about it, and how critically they engage with its outputs, matter more than is commonly acknowledged.

This is, honestly, where my own journey with this research lands. My discomfort with floundering in anecdotal arguments was not just about personal pride. It was about recognising that the conversations leaders have about AI, the way they frame it for their teams, the questions they do or do not ask, shape organisational culture around the technology. If those conversations are evidence-free, the decisions that follow them will be too.

The most practical starting point is developing genuine AI literacy rather than operational fluency alone. Knowing how to prompt a model is a useful skill. Understanding how training data affects outputs, what the limitations of a given system are, and when a tool is being used outside the domain where it performs reliably is a more important skill. The gap between those two states is largely a matter of deliberate effort.

Choose AI tools from providers who publish credible environmental and ethical accountability data. Where that data is not published, ask for it. That question, asked often enough, becomes a market signal. Be deliberate about when not to use AI. The AIHub review highlights a growing recognition that declining to deploy AI in certain contexts is a legitimate and sometimes correct ethical choice, not a failure to modernise. Building personal judgement about those boundaries is itself a form of literacy.

Bring evidence into team conversations rather than anecdote and assumption. Sharing credible sources, raising inconvenient questions, and being willing to sit with complexity rather than defaulting to comfortable narratives is a contribution any individual can make regardless of their seniority or technical background.

Pay attention to the efficiency of your own AI usage. Running repeated large queries for tasks that a simpler tool could handle has a real, if small, energy cost that accumulates across millions of users. Developing habits of proportionate tool selection is a modest act with aggregate significance.

Quick Wins: Where to Start This Week

The research can feel enormous in scope, but the entry points are practical and immediate. None of the following requires budget approval, a board decision, or a technical background. They are simply the actions of someone choosing to engage with this topic seriously.

For individuals:

Ask your AI tool of choice who made it, what energy it runs on, and whether the provider publishes environmental accountability data. The act of asking matters, even if the answer is incomplete. It builds your own literacy and sends a signal to the market.

Before defaulting to a large, high-powered AI model for a task, spend thirty seconds asking whether a simpler tool would do the job. Proportionate tool selection is one of the most immediate and overlooked ways individuals can reduce their personal AI footprint.

Read one piece of primary research on AI ethics or environmental impact, not a summary, not a social media post, but a full article or institutional report. The gap between what the evidence says and what most people believe it says is significant. Closing that gap personally is the first step to closing it in the rooms you operate in.

For teams and organisations:

Put ‘AI ethics and environmental impact’ on the agenda of your next strategy or leadership team meeting, not as a risk item to be managed but as a genuine conversation about values and governance. The AIHub ethics review from 2026 identifies the absence of structured organisational conversation as one of the primary reasons ethical AI deployment lags behind AI adoption.

Audit your current AI tool stack against two questions: does each tool serve a clear purpose proportionate to its cost, and does the vendor provide any transparency on energy and environmental data? You do not need to act immediately on the answers, but having them changes the quality of your next procurement decision.

Identify one AI use case in your organisation where a smaller, purpose-built model could replace a large generalised one. The energy saving at individual level is modest; the cultural signal of making that choice deliberately is considerable.

For leaders with broader influence:

Raise the question of mandatory environmental disclosure with any AI vendor you have a relationship with. The OECD’s measurement framework already provides the methodology; what is missing is the expectation from buyers that vendors use it.

Support or sponsor AI literacy investment in your organisation that goes beyond tool training. The difference between a workforce that can use AI and one that can think critically about it is the difference between adoption and governance.

The Productive Tension: A Genuinely Optimistic Conclusion

The research surveyed here, spanning environmental impact studies from Cornell, the OECD, and the Oeko Institute, ethical analyses from USC Annenberg and Stanford HAI, policy briefs from T20 India, the civil society report on AI climate claims, and the LSE Grantham Institute’s dual-perspective work, does not resolve into a simple verdict. But the fuller picture, including the evidence on extraordinary efficiency gains, accelerating renewable energy investment, and maturing ethics infrastructure, points somewhere more hopeful than the headlines typically suggest.

The numbers that initially gave me pause, the projections on exponential power and water consumption, are real. But so is this: AI model energy efficiency has improved by a factor of 100,000 over the past decade. Renewables accounted for over 90 per cent of new generating capacity in 2024, partly driven by the urgency that AI’s own energy appetite has created. AI is already reducing grid outages by 30 to 50 per cent and enabling cleaner energy integration at scale. The same technology creating the problem is actively contributing to the solutions, provided the deployment decisions are made consciously.

The sarcastic sign-off from the NotebookLM audio summary deserved its laugh, but it is not the final word. The research, taken in full, suggests that the negative impacts of AI are real, currently underestimated by most organisations, and genuinely mitigable. Not eventually, not hypothetically: now, with currently available tools, frameworks, and decisions. The three layers of responsibility described in this article, global policy, organisational governance, and individual accountability, are all moving. Not fast enough, but in the right direction, and with real momentum building.

The gap between the evidence and the average team meeting conversation about AI remains significant. But it is a gap that closes one conversation at a time: one honest question asked, one piece of primary research read, one procurement decision made with environmental accountability in mind. The scale of the challenge is not a reason for paralysis. It is a reason to start with the quick wins available this week, and to build from there with the seriousness the evidence deserves.

The AI reckoning is real. So is the opportunity to get this right.

If you are new here, I am Lee Whitmore, a leadership coach, author, and host of the LevelUp Leadership podcast. If you want a deeper, practical guide to leading in this landscape, my book ‘Enhanced Leadership’ goes further into the tools, mindsets, and conversations that help you and your organisation adapt. You can find it here: https://mybook.to/EnhancedLeadership

Until next time, keep leading, keep learning, and keep levelling up!

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References

1. Cornell University - “’Roadmap’ shows environmental impact of AI data center boom” (Nov 2025)
   https://news.cornell.edu/stories/2025/11/roadmap-shows-environmental-impact-ai-data-center-boom​

2. Oeko Institut - “Environmental Impacts of Artificial Intelligence” (Apr 2025)
   https://www.oeko.de/fileadmin/oekodoc/Report_KI_ENG.pdf​

3. International Science Council - “Considerations on environmental impact of AI in science” (Sep 2025)
   https://council.science/wp-content/uploads/2025/09/Considerations-on-the-environmental-impact-of-AI-in-science-FINAL.pdf​

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   https://arxiv.org/pdf/2507.21102.pdf​

5. OECD - “Measuring environmental impacts of artificial intelligence compute and applications” (Nov 2022)
   PDF: https://www.oecd-ilibrary.org/docserver/7ba4ec34-en.pdf

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   https://t20ind.org/wp-content/uploads/2023/07/T20_PolicyBrief_TF7_Environmental-Ethical-AI.pdf​

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9. Journal of Environmental Management - “The Two Tales of AI” (Sep 2025)
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12. USC Annenberg - “Ethical Dilemmas of AI”​
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