Quick answer: The 7 leadership AI mistakes I see every week, why they cost millions, and how founders are quietly avoiding them. Direct, no jargon.
By Andreas Petterson, founder of Leaders ADAPT and a former Canon executive who has built and scaled multiple companies.
A CEO emailed me last month. His company had spent two hundred thousand dollars on an AI rollout. The result was a Slack channel where his team posted screenshots of ChatGPT being clever, and a custom GPT nobody used.
He asked me a question I get almost every week. He asked me whether he should fire the consultant or fire himself.
I told him the truth. The consultant did what consultants do. The mistake was upstream of the tooling. The mistake was leadership.
I built a hyperscale AI platform at Arcules with one hundred and fifty employees before AI was a polite dinner topic. I have my own ADHD diagnosis and two sons on the neurodivergent spectrum, which is to say I have spent my life watching how the same situation produces very different outcomes depending on who is reading it. AI is no different. The technology is not the variable. The leader is. Most of the leadership AI mistakes I watch founders make are not technical. They are mistakes of identity, judgment, and pace.
Here are the seven I see most often, what they cost, and what to do instead.
Mistake 1: Treating AI as a Tool When It Is a Coworker
Most leaders adopt AI the way they adopted Slack. They install it, write a memo, and assume the team will figure it out. Then they wonder why nothing changes.
AI is not a tool in the Slack sense. It is more like hiring a new coworker who can do almost anything but needs to be told what good looks like. If you would not hire a senior analyst and then refuse to give them context, you should not roll out AI and skip the same step.
A Boston Consulting Group study from 2023 found that consultants using GPT-4 with proper framing completed tasks 25 percent faster and produced 40 percent higher quality work than those without it. The same study found that consultants using AI on tasks outside its capability produced work 19 percent more likely to be wrong. The tool was identical. The leadership around it was not.
Stop deploying AI. Start onboarding it.
Mistake 2: Delegating AI Strategy to Someone Who Has Never Run a P&L
This one is expensive. A founder hands AI to the most technically curious person in the room, usually someone in marketing or operations who likes tinkering, and asks them to come back with a plan.
That person comes back with a tooling list. They do not come back with a strategy. There is a difference.
Strategy is about which fights you stop having. Tooling is about which buttons you press. If the person you delegated to has never had to choose between two good options that both cost money, they cannot do strategy. They can only do shopping.
This is the part of the conversation where I tell founders something they do not want to hear. You cannot fully delegate AI strategy in the next eighteen months. You can delegate AI execution. The strategy has to live in your head, because the strategy is about how the entire company changes shape. That is a CEO question, not an IT question. That is exactly why the AI Mastermind exists. It is a room where founders learn AI as the discipline it actually is, not the workshop the rest of the market is selling.
Mistake 3: Hiring for the Clean Resume When You Need a Bilateral Thinker
AI automated the straight line. Anything that can be specified in a workflow with predictable inputs and outputs is now cheaper to do with a model than with a junior hire. That changes who you should be hiring.
The clean resume used to be a signal. Top school, top firm, clear progression. It signaled that the person had survived a series of selection processes that filtered for execution. Execution is the thing AI is now eating.
What does not get eaten is synthesis. Synthesis is the ability to hold three contradictory inputs in active tension and produce a decision that none of them obviously implies. I call the people who do this naturally Bilateral Thinkers. A Bilateral Thinker is someone who holds multiple ideas in active tension and synthesizes across them in real time, rather than executing a single linear plan. Many of them have ADHD. Many of them got fired from their first three corporate jobs for being too much. They are the people you now need on your AI strategy.
Stop hiring for the clean resume. Start hiring for the cognitive shape of the work that is left.
Mistake 4: Buying Pilots Instead of Picking a Direction
A pilot is a polite way of avoiding a decision. I have nothing against pilots in principle. I have a lot against pilots that exist because the leader cannot pick a direction.
The pattern is familiar. The leadership team agrees AI is important. They cannot agree on what it is for. So they fund six small experiments, hoping one of them will produce clarity. Eighteen months later they have six dashboards, no shipping product, and a finance team asking what they paid for.
AI does not produce clarity. AI compounds clarity. If you are clear about the bottleneck, AI is a force multiplier. If you are unclear about the bottleneck, AI is an expensive way to stay unclear. This is exactly what The Strategic Lens exists to solve. The Strategic Lens is a planning framework that forces a leadership team to name the one bottleneck whose removal would tap into the next twelve months of growth, before any tooling decision is made. Tooling without that question is theatre.
Mistake 5: Waiting Until It Is Safe
There is a version of caution that looks like wisdom and is actually fear. It sounds like, we are going to wait until the technology matures. We are going to wait until the regulatory picture is clearer. We are going to wait until our peers move first.
This is the most expensive sentence in business right now.
A McKinsey survey from 2024 reported that 65 percent of organizations are now regularly using generative AI in at least one business function, nearly double the share from ten months prior. The companies that waited until it was safe are now eighteen months behind companies that did not. Eighteen months in AI time is not a gap. It is a different category of business.
You are not waiting for it to be safe. You are waiting for it to be obvious. Those are different things. By the time it is obvious, the strategic option to differentiate is gone.
Mistake 6: Confusing Personal Productivity With Organizational Capability
The CEO uses ChatGPT for an hour a day. They draft emails, summarize documents, brainstorm with it. They feel like they are leading in AI. They are not. They are personally productive in AI. That is a different thing.
Organizational capability is what happens when a frontline person can do tomorrow what your best person can do today, because the system around them has been redesigned to absorb the leverage AI provides. That requires changes to hiring, to onboarding, to feedback loops, to how decisions are made. None of those changes happen because the CEO has a clever prompt library.
If you cannot point to a process in your company that runs measurably differently because of AI, you do not have AI in your company. You have AI in your laptop.
Mistake 7: Outsourcing the Question of What You Believe
This is the deepest one. AI forces every leader to answer questions they could previously avoid. What is this company for. Which work is sacred. Which roles deserve protection and which roles were always overhead the system was hiding. What kind of person we are going to be once we have this much leverage.
Most leaders try to delegate these questions. They hire a consultant to tell them, they ask a board to vote on them, they wait for an industry consensus to form. None of that works. The questions are not external. They are about what you actually believe about your company, your people, and yourself.
I had a health scare three years ago that forced me to answer some version of these questions about my own life. I learned something that applies directly here. The questions you avoid become the bottleneck you cannot name. AI is now compressing the timeline on every leader who has been avoiding their own.
What the CEO Who Emailed Me Did Next
The founder I mentioned in the opening did not fire the consultant. He did not fire himself either. He did something harder.
He sat down with his leadership team for two days and named the one bottleneck the company actually had. It was not AI. It was a sales process that depended entirely on his presence in every late-stage deal. Once they named it, the AI question answered itself. They built one workflow, not six, around removing him from the late-stage motion. Eight months later his revenue per rep is up 38 percent and he is no longer the constraint on his own company.
The expensive leadership AI mistakes are almost never about AI. They are about a leader being asked to grow up faster than they planned. The leaders who do it are quietly winning the next decade. The leaders who keep buying pilots are funding the comeback story they will tell at conferences in 2029, the one where they say they wish they had moved sooner.
Which version of that story are you writing right now?
The AI Mastermind is where leaders stop apologizing for how fast the ground is moving and start building companies that move faster than it.
If you are running a $1M to $10M business and you can feel that the cost of waiting is now higher than the cost of acting, this is the room. Explore the AI Mastermind. If you want to work on the underlying leadership question one-on-one, 1:1 CEO coaching is the deeper container.
Frequently Asked Questions About Leadership AI Mistakes
What are the biggest mistakes leaders make with AI?
The biggest leadership AI mistakes are not technical. They are strategic. Leaders treat AI as a tool to deploy rather than a coworker to onboard, they delegate strategy to people who have never run a P&L, they fund pilots instead of picking a direction, and they wait until it is safe to act. A 2024 McKinsey survey found that 65 percent of organizations now use generative AI regularly. The companies that waited are already behind.
How do CEOs avoid expensive AI mistakes?
CEOs avoid expensive AI mistakes by treating AI as a leadership question first and a technology question second. Name the single bottleneck whose removal would tap into the next twelve months of growth, then ask what AI workflow removes it. Frameworks like The Strategic Lens force that clarity before any tool is bought. Personal productivity in AI is not the same as organizational capability, and confusing the two is the most common expensive error.
What is a Bilateral Thinker?
A Bilateral Thinker is someone who holds multiple ideas in active tension and synthesizes across them in real time, rather than executing a single linear plan. The term was coined by Andreas Pettersson, founder of Leaders ADAPT, to describe the kind of leader whose cognitive wiring is now a competitive advantage in an AI-era market. Many Bilateral Thinkers have ADHD or other neurodivergent traits. AI automated the straight line, which means synthesis is the work that remains.
Should leaders learn AI themselves or delegate it?
Leaders should personally learn enough AI to set strategy, then delegate execution. You cannot delegate the question of how AI reshapes your business model, your hiring, and your operating system. That is a CEO question. You can and should delegate prompt engineering, workflow building, and tool selection. The Leaders ADAPT AI Mastermind is built specifically for founders who need to learn AI as a strategic discipline, not as a workshop.
Why do AI initiatives fail in most companies?
Most AI initiatives fail because they are launched without a named bottleneck. Leadership teams agree AI is important without agreeing what it is for, so they fund multiple small pilots in the hope clarity will emerge. Clarity does not emerge from pilots. Pilots compound the clarity that already exists. According to BCG research, AI applied to the right task produces 40 percent higher quality work, but AI applied outside its capability produces work 19 percent more likely to be wrong. The variable is leadership, not technology.
To go deeper, read ai-leadership-transformation-for-business-leaders, and why-ai-projects-fail-implementation-failure-analysis.
