I speak to leaders all the time who are panicking about artificial intelligence. They feel behind the curve. They read headlines about radical efficiency and worry their organisation is missing out on the future. This anxiety often leads to a frantic, disjointed pursuit of new tools.
In a recent episode of the Level Up Leadership podcast, I sat down with Ashley Gross, founder of The Alliance. She shared a compelling story of using automation to reduce her 80-hour working week down to just 15 hours. Her initial motivation was simple: she wanted to gain back time with her newborn son. Yet, what she learned when she scaled those same frameworks into an enterprise environment offers a sharp lesson for any leader navigating digital change.
The core tension we are facing with AI is not a lack of technological capability. The problem is that we are trying to use software to solve operational dysfunction.
If you layer a shiny new AI tool over a broken process, you do not get an optimised process. You simply get a broken process that moves much faster and breaks more spectacularly.
The Danger of Technical Debt
We are currently in a wild west phase of technology. We are placated daily with thousands of tools promising to revolutionise our work. In response, businesses are accumulating massive technical debt by chasing rapid experimentation without a clear strategy.
Leaders frequently bypass the platforms they already have in their existing tech stack to buy the next big thing. This creates fractured integrations and systems that refuse to talk to one another. Before you implement anything new, you have to audit your current reality. What are the problems you are actually trying to solve? Do you already pay for a tool that can do this?
In my book Enhanced Leadership, I explore the critical gap between strategy and execution. AI initiatives usually fail right in this gap. You cannot automate a workflow if you do not understand how it functions manually. When the AI eventually stumbles, you need to know how to repair the sequence. If your standard operating procedures are detached from the reality of the front line, bringing in an algorithm will only amplify the confusion.
Furthermore, successful implementation is rarely an IT challenge. It is a classic change management challenge. Friction happens because IT departments are left to manage the security and administration of tools that business units demand, all without the business leaders taking ownership of the operational risk, the training, or the workflow design.
Business leaders must bridge this gap. You need clear sponsorship, defined ownership, and documented contingency plans. When you have an agreed plan for what happens when things go wrong, the organisational anxiety drops significantly.
Implications for Leaders: How You Show Up
Your day-to-day behaviour dictates whether your team will successfully adopt new ways of working. You cannot expect people to experiment if the environment is built on fear and control.
Ashley pointed out a stark contradiction in modern management. You cannot demand that your team innovates and optimises their workflows if you simultaneously require daily status updates and anxious check-ins. If your management style relies on micromanagement, your team will never feel safe enough to test new ideas. They will treat the learning curve of a new tool as extra baggage rather than genuine leverage.
To lead effectively through this transition, you must:
Audit your processes first: Before buying software, map the workflow. Fix the bottlenecks manually.
Stop hovering: Provide clear alignment on outcomes, step back, and give your people the autonomy to figure out the execution.
Take ownership: Do not outsource the responsibility of AI adoption to your technical teams. Commercial leaders must own the risk, the training, and the results.
A Note for Coaches
When working with leaders navigating this transition, watch out for the panic response. Leaders under pressure often fixate on the technology rather than the human system surrounding it. Notice when a client is searching for a quick return on investment without defining the long-term goal.
Your role is to help them slow down and gain perspective. Ask them:
What exact operational problem are you trying to solve?
Do you have an AI problem, or do you have a process problem?
How is your own need for control impacting your team’s ability to experiment safely?
Help your clients see that their primary job is to create psychological safety and strategic clarity, not to become software experts. Guide them to articulate their five-year vision instead of reacting to immediate external pressures.
Conclusion
Artificial intelligence will change how we work, but it does not change the fundamentals of good leadership. Accountability, clear communication, trust, and robust process design are more important than ever. Technology is useless without intention.
Take a hard look at the processes you are trying to automate this week. Fix the dysfunction first. Ensure you are giving your team the space to learn without breathing down their necks.
If you found this reflection useful, I encourage you to listen to my full conversation with Ashley Gross on the Level Up Leadership podcast.
