What Does Expertise Look Like in the Age of AI?

AI Isn't Making Expertise Obsolete, it's Changing What Expertise Looks Like

For years, we've heard that mastering a skill requires thousands of hours of deliberate practice. Whether the number is 10,000 hours or something else, the message has been clear. Expertise is earned through experience, repetition, and continuous learning. Then along came AI.

Today, someone with very little experience can draft a report, build a presentation, summarize research, or analyze complex information in just a few minutes. It raises an interesting question. If AI can perform tasks that once took years to master, what does expertise look like now?

Much of the conversation about AI has focused on whether technology will replace human expertise. We think that's the wrong question. A better question is whether we've confused expertise with the work experts produce.

For years, the evidence of expertise was often found in the finished product. The person who could write the report, develop the strategy, solve the problem, or present the recommendation was viewed as the expert. Producing high-quality work required years of learning, practice, and experience, so it was a reasonable way to measure capability.

AI has changed that equation.

Today, technology can produce competent first drafts of many of those same deliverables in a fraction of the time. The quality can be surprisingly good, especially for routine or well-structured work. But producing a polished document isn't the same as exercising sound judgment, and that's where the conversation becomes much more interesting.

Think about the leaders you admire most. They aren't respected because they create the best presentations or write the best reports. They earn trust because they ask thoughtful questions, make sound decisions, coach others effectively, and help teams navigate uncertainty. What makes them effective has never been defined solely by what they produce. It's reflected in how they think, how they learn, and how they treat others and help them succeed.

The same principle applies across organizations. AI can organize information, identify patterns, summarize research, and even recommend next steps. What it cannot fully understand is the context surrounding those decisions. It doesn't know the history between two team members, the culture of an organization, or the competing priorities a leader is trying to balance. Those decisions still require human judgment, and they always will.

As technology becomes more capable, the capabilities that distinguish exceptional leaders become increasingly human.

Critical thinking becomes more valuable because someone still has to evaluate the information. Communication becomes more important because people still need clarity, direction, and confidence. Coaching becomes more meaningful because employees still need feedback and development. Trust becomes more essential because relationships cannot be automated. None of these capabilities are new. If anything, AI reminds us why they've always mattered.

The difference isn't AI. The difference is expertise.

Perhaps that's the real shift taking place.

For years, expertise was demonstrated by what we could produce on our own. Increasingly, it will be demonstrated by how effectively we think, guide, evaluate, and improve what technology helps us create.

The famous idea that mastery requires thousands of hours may not be obsolete after all. Those hours are simply being invested differently. We may spend less time learning how to produce every deliverable from scratch and more time developing the judgment to know what matters, what works, and what deserves our attention.

This shift also has important implications for leadership development. For years, organizations invested heavily in helping leaders build technical knowledge and functional expertise. Those investments remain important, but they may no longer be enough on their own. If AI reduces the time spent gathering information or producing first drafts, organizations have an opportunity to invest more intentionally in the capabilities that technology cannot replicate.

In many ways, AI may reduce the importance of teaching leaders what to think and increase the importance of helping them learn how to think.

Helping leaders think critically, ask better questions, navigate ambiguity, build trust, and develop others may become some of the most valuable work an organization can do. Perhaps that's what the future of expertise really looks like.

The tools we use will continue to evolve. They always have. The qualities that define exceptional leaders have been remarkably consistent.

Organizations will always need people who can think clearly, earn trust, develop others, and make wise decisions when the path forward isn't obvious. AI simply changes where those capabilities create the greatest value. It reminds us why they matter in the first place.

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If AI is changing what expertise looks like, it also challenges organizations to rethink how they develop leaders. Technical knowledge will always matter, but the human capabilities that drive trust, performance, and engagement have never been more important.

Join us for our complimentary webinar, Human-Centered Leadership: Supporting Leaders, Strengthening Performance, where we'll explore why developing leaders is one of the smartest investments organizations can make in an increasingly AI-enabled workplace. You'll leave with practical ideas for helping leaders think critically, build trust, coach effectively, and create the conditions where both people and performance can thrive.

Learn more and register today.