How to lead a team that knows more about AI than you do

Rowan Toffoli is  innovation and technology communications lead for AI, Lockheed Martin Corporation, and advisor, Ragan’s Center for AI Strategy. 

AI is changing how we work. It’s also changing how we lead.

Gallup recently found that 99% of CHROs believe AI is important to their organization’s strategy. But half aren’t confident their managers can effectively guide employees’ use of it. At the same time, OpenAI’s enterprise research shows that early-career employees are using AI more heavily than executives.

So, what happens when the people you manage become more fluent in a transformative technology than you are?

The answer isn’t for every manager to become an AI expert. It’s for managers to become better AI leaders.

Model curiosity, not expertise. Use AI yourself. Experiment with it. Share what works, and just as importantly share what doesn’t. Ask employees to share how they’re using it. Leaders who are willing to learn alongside their teams signal AI fluency is something we build together.

Bring everyone along for the journey. Allowing the gap between early AI adopters and everyone else to grow is a risk. Power users can be incredible catalysts for change, but only if their knowledge spreads to everyone. Give them opportunities to demonstrate workflows, mentor colleagues and share what they’re learning. Turn individual wins, like effective GPTs or Scheduled Tasks into team capabilities.

And pay particular attention to the people who aren’t raising their hands so you can discover and address their barriers.

Lead with EQ. AI adoption can be exciting, but it can also be uncomfortable. Employees may be worried about falling behind, looking inexperienced or even whether AI could eventually replace parts of their job. Managers need to create space for those concerns. Ask what people need. Listen without judgment. Build psychological safety around experimentation and learning.

Evaluate outcomes, not AI usage. As AI becomes part of everyday work, managers should focus on the quality of what employees produce. Is it accurate? Does it demonstrate critical thinking? Was sensitive information handled appropriately? Did a human apply judgment before hitting send? AI can assist the work, but accountability still belongs to the person doing it.

Turn experimentation into new ways of working. When an employee finds a better way to analyze data, draft content, conduct research or automate a repetitive task, don’t let that knowledge live with one person. Capture it. Test it. Teach it. Scale it. As a leader, it’s important for you to experiment with AI in your workflows, too.

For example, consider using AI to evaluate a feature story before it goes live to test sentiment and if key messages are pulled through. This is most effective when you test against a GPT (or similar) that has your brand’s voice and messaging context. When you get in the habit of using AI in your own workflow, you’re leading by example.

The organizations that succeed with AI will have more than the best technology. They’ll be the ones that build cultures where people are encouraged to learn, share and adapt together.

Managers have an enormous role to play in making that happen.

You don’t need to lead the AI adoption journey from the front every step of the way. But you do need to make sure everyone has a path to come along.