Don’t Let AI Turn Leaders Into Task Managers: How to Build Better Workplace Leadership

For decades, I have asked students in my leadership courses a deceptively simple question: What separates a leader from a manager? There is no single definitive response, but a common distinction is that leadership tends to be strategic, while management is often more operational and tactical. Artificial intelligence is poised to influence both roles, though not equally. As AI grows more capable of sorting information, streamlining workflows, increasing productivity, and suggesting what to do next, it reinforces many of the day-to-day tasks that managers already handle. Leadership, however, has always required a different kind of development. Strong leaders build judgment gradually by expanding their knowledge, challenging assumptions, spotting patterns, and making difficult calls when the right answer is unclear. If AI begins supplying answers before people have developed that deeper understanding on their own, organizations could become highly effective at creating efficient managers while falling short on cultivating strategic leaders. That is a serious concern because businesses win through innovation, agility, and sound decision-making, all of which depend on capable leadership.

Why Leaders Develop Differently Than Managers

So how does a person truly become a leader? In my view, it is not simply the result of earning a title or collecting a large amount of information. Leadership develops over time, through accumulated knowledge, repeated problem-solving, and exposure to enough varied situations that people begin to notice things they likely would have overlooked earlier in their careers.

Over the years, I have interviewed thousands of executives, founders, researchers, psychologists, and business leaders, and I have often asked how they handled difficult decisions. Their responses varied widely, but one theme consistently emerged: the judgment they relied on had been shaped over a long period. They pulled from prior roles, meaningful conversations, books, research, mentors, wins, setbacks, and lessons gathered across their professional lives. That accumulation of experience helped them detect patterns and frame stronger questions. To me, that slow, layered process has always been central to developing as a leader.

When I spoke with Stella Collins, cofounder and Chief Learning Officer at Stellar Labs and author of Neuroscience for Learning and Development, she pointed out that people often mistake access to information for actual learning. AI can deliver information almost instantly. Learning still demands reflection, practice, context, and enough time to understand why an approach succeeds in one circumstance but breaks down in another. A summary can introduce someone to a subject. Developing the judgment to know when that summary leaves out something important takes far longer.

I see the same thing in my own work. Research from my dissertation on emotional intelligence still influences projects I work on today. Interviews from my radio show continue to help me develop ideas for Forbes articles years after those conversations took place. I might be writing about curiosity and suddenly remember something a CEO said years ago. Other times, a psychologist’s comments help explain a leadership challenge. Those connections were never planned. They happened because knowledge continued to build over time. I think leaders develop in much the same way.

Why AI May Change How Leaders Develop

I use AI every day because it saves me an incredible amount of time. I also know that the first answer it gives me is rarely the end of my research. More often than not, it sends me looking for another source, another opinion, or another question. That is where much of the learning still takes place.

When I interviewed entrepreneur and New York Times bestselling author Josh Linkner, we talked about innovation, and he explained that original ideas come from continuing to explore after most people believe they already have the answer. Leadership develops in much the same way. Throughout my interviews, the leaders who impressed me the most were willing to keep asking questions long after everyone else was ready to move on.

That is where I see a possible unintended consequence of AI. Managers benefit immediately because AI helps them complete many of the responsibilities they already have. Leaders benefit too, but leadership has always depended on building enough knowledge to recognize when an answer deserves another question. If employees become accustomed to receiving conclusions before they build that understanding for themselves, organizations could gradually develop people who become very good at managing work without developing as many people who naturally grow into strategic leaders.

Another issue deserves more attention than it receives. AI responds to the assumptions built into the prompt. If those assumptions are weak, the answer often builds on them. One of the easiest ways to improve the quality of AI’s responses is to ask it where your thinking could be wrong, what assumptions deserve another look, or what someone with a completely different viewpoint might say. Those questions often produce much better discussions than simply asking AI for an answer.

How Organizations Can Continue Developing Leaders

Leadership development may need to become more intentional than it has been in the past. Teaching employees how to use AI effectively is important. Teaching them how to think alongside AI may become even more important.

One approach is to have people work through an issue before opening AI. Ask them how they reached their conclusion, what information they relied on, and what assumptions they made. After AI responds, compare its recommendations with the team’s thinking. The discussion should focus less on whether AI was right and more on why the answers were different. Those conversations help people build the kind of thinking that organizations expect from leaders.

Organizations may also want to take another look at what they recognize and reward. AI is going to help almost everyone become more efficient. Efficiency alone is unlikely to distinguish future leaders. Employees who ask thoughtful questions, challenge assumptions respectfully, connect ideas from different disciplines, or recognize opportunities others overlook may create even greater value as AI becomes part of everyday work. Those are also many of the same qualities organizations have traditionally looked for when identifying future leaders.

Why The Future Still Needs Leaders

AI is one of the most valuable business tools I have seen during my career, and organizations should absolutely embrace it. The opportunity is making sure it becomes more than a productivity tool. Managers and leaders have always played different roles, and organizations need both. AI is likely to strengthen management first because efficiency is exactly what it was designed to improve. Leadership develops over a much longer period of time through learning, experience, curiosity, and the ability to recognize that the first answer is not always the best one. Organizations that continue creating opportunities for people to build that depth of understanding while taking full advantage of AI may be the ones that develop both stronger managers and stronger leaders.