As AI makes knowledge instantly accessible, leadership is shifting from providing answers to creating judgment, meaning and learning.
AI can expand what an organization knows. Learning-agile leadership determines what the organization is capable of becoming.
For much of organizational history, knowledge moved through hierarchy. The people at the top had greater access to information, broader exposure to the business and more authority to interpret what it all meant. Leaders were expected to know more, see further and provide answers. Understanding leadership in the age of AI begins with recognizing how dramatically access to knowledge has changed.
Artificial intelligence is breaking that relationship between knowledge and position. An employee can now research an unfamiliar market, compare strategic options, interrogate a dataset and produce a credible first draft before a meeting begins. Expertise has not disappeared, but access to an expert-like answer is no longer scarce.
That creates an uncomfortable question: when answers are everywhere, what is a leader for?
The answer is not that leaders have become less necessary. It is that one kind of leadership has become less valuable: leadership whose authority depends primarily on knowing more than everyone else.
Leadership was never located in the leader alone
Long before AI entered the workplace, W. Warner Burke was challenging the idea that leadership could be explained by the qualities of the person at the top. In a 1965 article, he described leadership behavior as a function of the leader, the follower and the situation. Leadership, in other words, emerges from an interaction. It is not a possession that one individual carries into every context unchanged.
Six decades later, AI is changing that interaction. It changes what people can know without asking their manager. It changes the speed at which ideas can be generated and challenged. It changes where useful expertise can be found. And it changes what employees reasonably expect from the person leading them.
If the situation changes, leadership behavior must change with it. A leader who continues to act as the principal source of answers may inadvertently slow the organization down. Worse, the leader may create dependence at the precise moment when the organization needs more people capable of thinking, questioning and learning for themselves.
AI can provide an answer. It cannot provide organizational meaning.
This distinction becomes clearer through another important contribution from Burke’s work. The Burke-Litwin model proposes that changes in the external environment affect transformational elements of an organization, including its mission and strategy, leadership and culture. These, in turn, shape systems, management practices, climate, motivation and performance.
AI is unquestionably an external disruption. But adopting an AI platform is not the same as transforming an organization. Someone still has to interpret what the technology means for the purpose of the business. Someone has to decide which values should constrain its use, which risks are acceptable, what capabilities people will need and what should remain distinctively human.
AI may generate ten plausible strategic options. It cannot decide what the organization is prepared to stand for. It cannot create trust among people who are anxious about their relevance. It cannot take responsibility for the consequences of a choice.
That is not a small residual role left over after the technology has done the important work. It is the important work.
The scarcity value of leadership has moved
When information was scarce, leaders created value by supplying it. When answers become abundant, leadership value moves upstream and downstream of the answer.
Upstream, leaders help people frame the problem. They ask what is actually at stake, which assumptions are shaping the question and whose experience may be missing. Downstream, they help people exercise judgment: Which answer is credible? What does it mean here? What are the unintended consequences? What should we try, observe and learn next?
This requires expertise, but it is a different expression of expertise. The future-ready leader does not use experience to end the conversation. The leader uses experience to improve the quality of inquiry.
That difference matters. In an uncertain environment, yesterday’s pattern can be a useful clue or a dangerous constraint. Leaders must know when their experience is relevant and when it is preventing them from seeing something new.
Leadership in the Age of AI: The Leader as an Architect of Learning
This is where Burke’s later research on learning agility becomes especially powerful. In Learning Agility: The Key to Leader Potential, David Hoff and Warner Burke argue that learning agility can be understood through observable behaviors rather than treated as a vague openness to change.
Learning-agile people seek information and feedback. They experiment, reflect and adjust. They are willing to take performance and interpersonal risks. They involve other people in their thinking instead of protecting the appearance that they already know.
These behaviors are even more consequential in the age of AI. The quality of a generated answer depends partly on the quality of the prompt, but the quality of a decision depends on much more: the leader’s willingness to challenge the output, search for disconfirming evidence, invite other perspectives, test an assumption and learn from the result.
AI can accelerate the acquisition of information. Learning agility determines whether that information becomes better judgment—or merely faster certainty.
The leader as an architect of learning
The most important change may be from answer-giver to learning architect. Instead of making themselves indispensable to every decision, leaders create the conditions in which more people can exercise judgment and grow.
They frame questions without dictating conclusions. They make it safe to say, “I may be wrong.” They ask what was learned, not only whether the target was met. They expose emerging leaders to unfamiliar assignments while providing enough support for reflection. And they model the feedback-seeking and experimentation they want others to practice.
This is also how organizations avoid one of the hidden dangers of AI: the erosion of the experiences through which future leaders develop. If early-career work is automated without being redesigned, people may become more productive while losing opportunities to struggle with ambiguity, make judgments, receive feedback and build confidence.
A learning architect does not preserve low-value work for its own sake. The leader deliberately creates new developmental experiences: simulations, stretch decisions, cross-functional problems, client exposure, after-action reviews and opportunities to test ideas with real consequences.
Four questions for leaders now
Am I providing the answer too quickly? A fast answer can solve today’s problem while preventing someone else from developing tomorrow’s judgment.
What are we learning, not only producing? AI may increase output without increasing capability. Leaders need to pay attention to both.
Where does human judgment matter most? Not every decision deserves the same degree of human attention. Leaders must identify the choices involving meaning, ethics, relationships and consequential uncertainty.
What behavior am I modelling when I do not know? The future culture of leadership is shaped by whether senior people become defensive—or curious—when expertise reaches its limit.
Leadership is not becoming obsolete. It is becoming more visible.
When a leader can no longer rely on privileged access to information, we see more clearly what leadership contributes. It creates direction without pretending to eliminate uncertainty. It connects external change to mission and culture. It enables other people to think, act and learn. And it accepts responsibility for judgment when no available answer is complete.
I find that prospect hopeful. It asks leaders to become less invested in appearing certain and more committed to creating collective capability. It also gives organizations a more useful way to identify potential: not by asking only who knows the most today, but by observing who continues to learn when knowledge, conditions and expectations change.
Warner Burke’s work has traced this idea across a remarkable span of time. Leadership is situational. Organizational change is systemic. Potential is revealed in the way people learn from experience.
When answers are everywhere, the leader is not the person who brings every conversation to a close. The leader helps the organization ask better questions, exercise wiser judgment and become more capable because the conversation took place.
AI can expand what an organization knows. Learning-agile leadership determines what the organization is capable of becoming.
Sources and further reading
Burke, W. W. (1965). Leadership Behavior as a Function of the Leader, the Follower, and the Situation. Journal of Personality, 33(1), 60-91. View source
Burke, W. W., & Litwin, G. H. (1992). A Causal Model of Organizational Performance and Change. Journal of Management, 18(3), 523-545. View source
Hoff, D. F., & Burke, W. W. (2017). Learning Agility: The Key to Leader Potential. Hogan Press. View source
Burke, W. W. (2023). Organization Change: Theory and Practice (6th ed.). SAGE Publications. View source
Teachers College, Columbia University (2013). 3 Questions with Warner Burke. Teachers College. View source
