How to Lead Your Team When AI Becomes the Smartest One in the Room

Unless you’ve been living under a rock, you probably noticed that AI is everywhere. Chances are, you’ve probably also missed a lot of where AI is showing up--and this probably happened without giving you much notice.

Naturally - this has become a leadership issue.

I have read, I have listened, and I’ve watched numerous thought leaders on numerous platforms talking about this as a disruptive force. But, one thing seems to be true: the thought leaders who are talking about this issue consistently fall short of giving leaders actual actionable insight to lead differently.

Most are focused on developing mindset, AI doesn’t change that - your team needs to be ready to learn already, structures and governance need to exist to ensure proper usage, or we need to be building better AI to navigate responsibilities, ethics, or align with values. I have yet to see anyone discuss how to actually lead when AI has become a part of how your team operates. In essence - when AI has become a part of your team.

This article can help you do that.

My goal is to shift your thinking about AI so you can be thoughtful about your own solutions-- and provide you with some of my own.

So let's start here: What's the problem that nobody is talking about?

AI presents a high-performer problem - a problem leaders struggle with but rarely name.

In his book “Can’t Hurt Me” David Goggins describes with great detail the “boat test” done at the end of “hell week” which is part of the training to become a United States Marine. I’m not a fan of military analogies for the work place but in this case it can help you understand the impact of AI on a team. 

After grueling training, prospects are asked to fill a boat with water and hold it - as a team - over their heads and overcome various obstacles and tasks. Tasks that sound simple - like hold the boat above your head, very quickly become an exercise in agony and endurance. In his book this would become a defining moment of struggle and lessons for David. During year one he describes simply not being strong enough, having plenty of grit but a body and mind that wasn’t fully prepared. It was the next year, a year that still ended in failure where the comparison to AI on a team became truly relevant.

As the tallest person in his team of prospects he lifted the boat as high as possible - yelling encouragement and giving his all. Mind strong, body prepared and yet, the team failed. Why? 

It was simple - the tallest crushed the smallest. 

As the water continued to shift onto the arms of the shortest of the boat team the smallest obstacles became insurmountable, soon they were crushed into submission. Soon they rang the bell symbolizing their choice to leave the program. Then another. Then it was simply too much effort for the remainder to succeed. The rest of the boat team failed.

Failure of the team was caused by an over achiever outperforming the rest.

Success came to David and his boat crew when he submitted himself to the torment of hell week again and learned that the whole team needed to succeed for any one of them to succeed.

This is a challenge very few leaders handle well. Often leaders will try to ignore, exploit or diminish for the sake of their own ego the highest performer on the team. The challenge is giving them a place to excel without allowing their capacity to crush the more average players.

The best leaders know how to enable the highest performer to elevate the whole team - not just themselves.

This is the challenge of AI that nobody is really talking about.

It is the highest performing, smartest person you’ve had on your team. And unlike a human - it doesn’t care either way - it’s neutral. 

Like every single high performer out there - AI has limitations. 

If you are trying to lead a team without addressing the high-performer elephant you’ll slowly lose ground and eventually your relevance.

I’ll talk about how to manage this better as you read - but first we need to talk about what happens to the team so you can course correct effectively.

When you have an imbalance on a team three things happen:

Step 1: Deference. 

As people start to realize how capable AI is they often start to simply defer to the AI. They submit, often humbled by its capacity.

“Its always going to be smarter than I am so why would I even try?”

This is where it starts... But it’s not where it ends. As this habit forms there is research emerging from MIT that shows how concerning this is. 

When people lean on AI like ChatGPT to complete tasks, their brains simply work less. Participants monitored by EEG who were asked to write SAT-style essays with ChatGPT showed the lowest cognitive engagement compared to those using Google or no tool at all. Over time, many stopped thinking through their answers entirely, defaulting to copy-and-paste from AI outputs. The way this study was set-up and the parallels it draws to so much of the work people do makes the finding hard to dismiss. 

Not only are there new habits being formed - the brain in a sense is becoming de-formed as parts of the brain begin to shut down.

Not a good recipe if you want the best out of the people on your team.

The convenience of AI will train your team to hand over the hard thinking and quietly shift towards deference. 

This silent shift is the one you need to watch for. But it doesn’t end there…

Step 2: Learned Helplessness 

This is a psychological phenomenon where individuals become passive and give up. Particularly when they could change a situation from bad to good, even when opportunities are available. 

This happens when there is repeated exposure to uncontrollable negative events. In the case of AI, it's the feeling of being stupid, outshined, or simply when the feeling of awe trunks being humbled into being humiliated. The lack of ability to change the situation as mere mortals can perpetuate the desire to simply submit.

This is a challenging space to be in because this is the moment where white-collar workers in particular will begin to be replaced. When a team has moved into this mode of thinking it’s because they have not built guardrails - but they also haven’t built a way to capture the talents of the humans in the room - or the AI at their fingertips.

Step 3: Falling through the same Gaps

At this point the challenges can quickly create a wider, or more systemic issue. On a team where there is a standout star or high performer who is able to accomplish more than the others, very simple things happen. The rest of the team stops looking and the natural gaps and failures of the high performer become the gaps that everyone falls through unless they are aware and keep their eyes open. A good team, and good collaboration can cover the gaps. 

Without collaboration AI's gaps become the team's gaps.

In sports, the narrative is often “a good defense vs a great offense” because it is a real challenge to be completely focused on offense without leaving a gap. The greatest hockey player of all time, Wayne Gretzky, was able to play more offence, shoot the puck more, and play a more fluid game because there was always an enforcer on the team who would go on the attack if the opposing team did anything to hurt him.

Someone on the team was there to fill the gap that was left open because of such a strong focus on a different aspect of the game.

A great salesperson might sell well but not collaborate well with an engineering team. A great architect might be able to name all the building codes but bad solutions. A lawyer might be able to identify risks in a contract but struggle to communicate risk to a client.

So, for a little fun, I thought I would ask ChatGPT about its limitations - Where can AI fail where a team of people can succeed? My own notes are in the brackets.

• Emotional Intelligence & Empathy - AI can fake “I understand,” but it doesn’t feel anything. Humans feel. That’s how trust gets built. (this makes me think about Client interactions in particular, emails, and interactions)

• Ethical Judgment in Ambiguity - When the rules are fuzzy, humans can weigh values. AI just follows instructions. (This makes me think about risk analysis but more often - risk tolerance)

• Creativity From Lived Experience - AI mashes up what’s out there. Humans create from what they’ve lived. (Experience matters - AI doesn’t accommodate for reality the same way we would, nor can it account for what we omit from our requests)

• Sense-Making in Complex, Changing Contexts - Humans can read the chaos, connect the dots, and reframe on the fly. AI needs a prompt. (complexity is where humans can thrive - complicated is for AI)

• Building Trust & Influence - AI can answer questions. Only humans can earn belief. (No amount of AI can build momentum, buy-in or influence - humans are necessary - they need to build to believe)

Each of these present their own problems. One of those problems is that each of these gaps will remain hidden if you and your team leave their potential impact unaddressed.

Leadership is the Key

Leading a team of high performers is relatively easy. You let them run and make sure they know what the target is. A group of average performers with good leadership can become a high performing team as well with the right focus, framing and support.

Leading a team where there is a large discrepancy in talent is hard - whether that person is capable - or incompetent.

When you are leading a team where someone is difficult or lacks competency - the team will often pick up the slack. You can offer training and many other methods of motivation, alignment with values and sometimes - removing them.

The answers are a bit more clear.

But, a high performer can be more of a double edged sword.

You need to provide lanes where they can run, and areas where they can bring others up with them instead of trampling on them.

This applies to high performing people - and AI.

So, what are the solutions?

Practically speaking, to lead a team with one or a very small minority of high performers, you want to leverage their talent without letting the rest of the group slip into passive support roles. 

There are many ways you could approach this problem but I want to focus on three.

Framing

Framing and reframing are the main skills here. It sounds simple - but it is critical and often ignored. 

You need to create a shared set of assumptions and beliefs that empower everyone on the team. In particular that means creating clarity around purpose, uncertainty, interdependence, failure, roles and what’s at stake so that everyone can contribute effectively and learn together. 

The high performer can be given stretch assignments or complex problems that inspire the team (places to run), but they should also be encouraged to mentor, share processes, and lift others’ capabilities (opportunities to raise others up). As the leader, your job is to make sure success is seen as a team achievement, not a solo act — keeping morale high, skills growing, and ownership evenly distributed so no one becomes dependent on the star. 

The high performer needs to develop their team and leadership skills. You don’t want them to patronize, you want them to give them the skills to highlight the moments of brilliance around them.

Thankfully, most of this transfers to how you lead a team that could easily defer to AI.

Yet, it is essential you name that it would be a failure if the team starts to defer to AI and develop a pattern that would lead to learned helplessness. 

You need to Leverage AI rather than succumbing to it - and you need to make that part of the teams work. 

This is where setting and maintaining boundaries becomes critical. Leaving people feeling like they don’t matter, can’t contribute, or can switch off their best thinking

Boundaries

Boundaries need to be established around time, place, best use and evolving use.

Think about WHEN in a process using AI will empower or disempower a team. Think about what topics AI is best suited for (complicated issues) and what human collaboration is best suited for (complex issues). Think about WHAT the best use is and how your team can build on what the AI offers instead of lowering to it’s limitations. Think about HOW the team will assess usage so that it is helpful but not replacing their thinking. 

So, how can you use AI most effectively with less risk while keeping ownership, agency and collaboration with the team?

Again, I thought this would be an interesting question to work through with ChatGPT. You can ask similar questions and discuss answers with your team to get the most, or avoid the traps of AI specific to your work.

1. Gap Analysis & Opportunity Spotting: AI can scan projects, processes, or datasets to identify where performance, quality, or coverage is falling short.

• Example: Feed AI project summaries and metrics, and have it highlight skill gaps, missed market opportunities, or recurring bottlenecks for the team to address.

• How it avoids dependency: The AI flags the gaps, but the team designs the fixes — ownership stays with them.

2. Scenario Modeling & What-If Analysis: Use AI to rapidly simulate possible outcomes so the team can make better strategic choices.

• Example: Model how shifting budget between two marketing channels might affect reach and conversion, or how changes to workflow impact delivery times.

• How it avoids dependency: AI provides the models, but humans decide which to pursue and why.

3. Pattern Recognition in Messy Data: AI excels at spotting trends, anomalies, and correlations in large datasets that the team can then investigate.

• Example: Have AI find unusual spikes in customer complaints, subtle shifts in engagement patterns, or early signs of market changes.

• How it avoids dependency: AI points to the signal; the team does the sense-making.

4. Drafting & Pre-Work for Efficiency: Use AI to create a structured starting point for reports, briefs, or presentations so the team can spend more time on refinement and insight.

• Example: AI produces the first draft of a competitive landscape report; the team updates it with on-the-ground knowledge and strategic recommendations.

• How it avoids dependency: AI gets the team to the starting line faster — they still run the race.

5. Rapid Synthesis of Conversations: AI can distill long, complex discussions—like discovery calls, stakeholder interviews, or meeting transcripts—into concise project proposals, customized brochures or executive summaries in minutes.

• Example: Feed AI a 60-minute client call recording and have it produce a bullet-point brief highlighting needs, priorities, and next steps.

• How it avoids dependency: AI captures and organizes the content; the team applies judgment, nuance, and strategy before delivering.
  

These areas, along with many others, are areas to leverage AI - but the key is to keep your eyes open to the fact that it can cause the steady decline in the capacity of your team. 

Facilitation

Facilitation is the often ignored or un-considered leadership skill of guiding how people work together — especially when AI is in the mix. It’s not just running a meeting, it’s about creating the conditions where contributions surface, ideas emerge, and ownership is shared. In a team that could easily defer to AI, your role is to actively shape the flow of interaction so humans stay engaged with each other, not just with the tool.

That means prompting discussion before revealing AI’s output, inviting multiple interpretations of its suggestions, and assigning people to challenge or build on what AI offers. Start with human perspectives, bring AI in as a high-performing collaborator, then return to the team for sense-making and decision-making.

Good facilitation of time together and shared effort turns AI from an answer machine into a tool that sparks deeper human thinking rather than replacing it. Your facilitation can ensure that AI leads to progress without eroding curiosity, dialogue, or the shared responsibility to get the work right.

Framing keeps the team together, focused, aligned and adaptive. Boundaries that are well maintained and well informed will keep the team on track and avoid pitfalls. Your facilitation will help you manage both at a team level and ensure that you are capturing the voices and wisdom of your team.

Your leadership is as critical as it has ever been - AI is just a new element to learn.

If you build psychological safety and focus your team in the right direction of shared ownership and accountability you will embolden the capacity to learn through any challenge - including AI.