AI Doesn't Change the Most Important Leadership Question
Every endurance athlete eventually learns an important lesson.
When training starts paying off and your aerobic engine gets stronger, there is a temptation to simply train more. Ride another hour. Add another interval. Fill every available minute with more work.
Ironically, that's often the moment progress slows down.
Experienced athletes know that improved fitness is not a reward to be spent. It is a resource to be invested wisely.
Sometimes the smartest decision isn't another training session.
It's recovery. It's refining technique. It's improving nutrition. It's studying race tactics. It's preparing for tomorrow rather than exhausting yourself today. The goal was never to maximize training volume. The goal was always to maximize performance.
I have the feeling that organizations are about to face exactly the same challenge.
The Wrong Question
Artificial intelligence promises significant productivity gains for knowledge workers.
Software developers write better code faster. Business analysts summarize information in minutes instead of hours. Project managers automate documentation and reporting.
Every new study seems to ask the same question:
How much productivity can AI create?
That is certainly an interesting question. I am no longer convinced it is the most important one.
The more interesting question is:
What should leaders do with the productivity AI creates?
Mastery or Results?
How gains in productivity should be utilized led me to another question:
What should leaders prioritize in the age of AI: mastery or results?
Initially, this looked like a difficult trade-off. Organizations exist to create results and not to breed lots of experts. But sustainable results depend on capable people. The more I explored the question, however, the more I realized it rests on a false assumption. AI does not reduce the importance of mastery. It changes what mastery looks like.
A software architect has never been valuable because they could draw architecture diagrams. They create value because they understand technology, economics and business well enough to design systems that should exist.
A business analyst's real contribution is not writing requirements. It is recognizing patterns, anticipating developments and helping organizations prepare for an uncertain future.
A project manager's value has never been the creation of a project plan itself. It lies in understanding dependencies, balancing stakeholder interests and adapting when reality inevitably changes.
AI increasingly produces the artifacts of knowledge work. The human contribution remains the thinking and the judgement that comes before them.
The New Nature of Mastery
For decades, expertise was visible. You recognized it through reports, presentations, spreadsheets, documentation and carefully crafted project plans. Today, AI can generate many of those outputs in minutes. The artifact no longer proves expertise. The quality of the underlying thinking does.
Perhaps the future of mastery is less about knowing more facts than about consistently exercising better judgment. That doesn't make knowledge less important. It simply moves the competitive advantage further up the value chain.
Instead of asking:
"Can this person create an impressive deliverable?"
leaders may increasingly ask:
"Can this person consistently make better decisions?"
What Should Leaders Develop?
Knowledge still matters. Technical expertise still matters. But AI changes where leaders should invest their attention.
The capabilities that may become increasingly valuable are surprisingly human:
Systems thinking
Critical thinking
Problem framing
Sensemaking
Effective communication that is tailored to the recipient
Continuous learning and empathy
Judgment
These capabilities help people distinguish signal from noise, identify the right problems before solving them and understand second- and third-order consequences.
Ironically, AI may increase—not decrease—the value of these skills.
Productivity Is Not the Goal
This brings me back to endurance training. Athletes don't become world-class because they maximize training hours or distances. They become world-class because they convert training into adaptation. The strongest athletes understand that every improvement creates choices. They can spend their additional capacity immediately. Or they can invest it wisely to become even stronger tomorrow.
Organizations now face the same decision. If AI saves an hour, leaders can immediately fill that hour with another meeting, another report or another project.
Or they can invest that capacity in mentoring, learning, experimentation, technical debt reduction, customer conversations, strategic thinking and innovation.
One path maximizes activity. The other builds capability.
Those choices will likely matter far more than the AI tools themselves.
The Leadership Question
Perhaps the organizations that benefit most from AI will not simply be those that automate the fastest. They will be those that most deliberately convert productivity into new organizational capability.
That, ultimately, is not an AI challenge. It is a leadership challenge.
And therefore that really is the one important question leaders should ask themselves over the coming years:
If AI makes our organization X% more productive, what should we do with the X%?
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