How the AI Revolution Is Changing Leadership: Five Priorities for Leadership Development

Will increasing employees’ AI proficiency automatically improve organizational performance?

As AI adoption accelerates, many organizations are investing in AI training. Yet being able to use AI and creating new value through AI are two very different things.

As AI takes on analytical, advisory, and other knowledge-intensive tasks, what capabilities will leaders need to succeed?

The AI revolution is not simply a technological challenge. It is also a leadership challenge.

1. From the IT Revolution to the AI Revolution: How Is the Leader’s Role Changing?

The IT revolution transformed organizations through digitization, information sharing, and operational efficiency.

Leaders were expected to use technology to standardize processes, improve productivity, and manage people and operations effectively.

The AI revolution represents a different kind of transformation.

AI can now perform tasks that previously required human intelligence, including analysis, reasoning, generating recommendations, and executing certain activities.

As a result, the role of leaders is expanding.

During the IT revolution, the central question was how people could use technology to perform their jobs more effectively.

In the AI revolution, the question is how people and AI can work together to create value that neither could achieve alone.

What does this mean for leadership development?

2. Five Leadership Capabilities for the AI Era

1. From Providing the Right Answers to Asking the Right Questions

AI can generate multiple solutions to a given problem.

However, identifying the problem that truly needs to be solved remains an essential human responsibility.

For example, a leader might ask AI:

“How can we reduce the time required to prepare reports by 50%?”

AI may suggest several ways to streamline the process.

But a different question could lead to a more significant transformation:

“Why do we need this report in the first place?”

By challenging the underlying assumption, the leader may discover an opportunity to eliminate or fundamentally redesign the reporting process.

In the AI era, effective leaders must do more than solve problems. They must also question how problems are defined.

2. Designing Effective Collaboration Between People and AI

Traditionally, leaders assigned work according to employees’ knowledge, experience, and capabilities.

Today, they must make an additional decision:

Which tasks should be performed by AI, and which require human judgment, creativity, and interaction?

Consider a sales organization.

AI can analyze market data, identify patterns, and summarize customer information.

Sales professionals can then devote more time to understanding customers’ unspoken needs, building relationships, and developing innovative solutions.

The objective is not simply to reduce workloads through automation.

It is to redesign work so that people can contribute greater value.

3. Evaluating AI Recommendations and Taking Responsibility for Decisions

AI can process enormous amounts of information and generate convincing recommendations.

However, its outputs may contain inaccuracies, biases, or questionable assumptions.

For example, AI might analyze employee performance data and recommend candidates for promotion.

A responsible leader would not automatically accept those recommendations.

Instead, the leader would examine the fairness of the evaluation criteria, potential data biases, and relevant individual circumstances before making a decision.

AI may support decision-making, but accountability remains with people.

Leaders must therefore develop the ability to use AI confidently while critically evaluating its recommendations.

4. From Improving Existing Processes to Reimagining Work

The IT revolution emphasized making existing processes faster, more accurate, and more efficient.

The AI revolution creates opportunities to question whether those processes are necessary at all.

Using AI to produce a sales report in half the time is an operational improvement.

Redesigning the information-sharing process so that salespeople no longer need to prepare the report—and can spend more time engaging with customers—is a transformation of work.

AI-era leaders must be able to envision new ways of working rather than simply improve existing ones.

5. Developing People Who Can Think and Learn Alongside AI

AI gives employees unprecedented access to information, expertise, and analytical support.

Yet if employees simply accept AI-generated answers, they may have fewer opportunities to develop their own thinking and judgment.

This makes leadership coaching even more important.

When an employee presents an AI-generated analysis, a leader might ask:

“What aspects of the AI analysis do you question?”

“Are there customer circumstances the AI may have overlooked?”

“What would your own judgment be?”

Such questions encourage employees to examine evidence, challenge assumptions, and develop independent judgment.

The leader’s role is no longer primarily to provide answers.

It is to help others become better thinkers and decision-makers.

3. Why Extraordinary Leadership Matters Even More in the AI Era

The AI revolution creates new leadership demands.

However, it does not make established leadership capabilities obsolete.

In a 2026 study, Zenger Folkman examined more than two million leadership assessments involving 138,777 leaders to explore the importance of human-centered leadership capabilities in the AI era.

Three capabilities were particularly significant:

• Developing Others
• Inspiring and Motivating Others to High Performance
• Building Relationships and Trust

For example, leaders in the bottom quartile for Developing Others averaged the 21st percentile in overall leadership effectiveness.

Leaders in the top quartile averaged the 85th percentile.

That represents a difference of 64 percentile points.

These findings demonstrate a strong relationship between developing others and overall leadership effectiveness.

The research also highlighted an important gap: inspiring and motivating others was among the weakest leadership capabilities in observed performance, even though direct reports considered it especially important to their success.

As AI increasingly supports analytical and operational tasks, the human capabilities of developing people, inspiring commitment, and building trust become even more valuable.

AI has not made the fundamentals of extraordinary leadership irrelevant. It has made them more important.

4. Applying the 19 Competencies of The Extraordinary Leader™ in the AI Era

The Extraordinary Leader™ identifies 19 leadership competencies and uses 360-degree feedback to help leaders understand their strengths and development opportunities.

Preparing leaders for the AI era does not require replacing these competencies.

Instead, organizations need to identify how established leadership capabilities should be demonstrated in workplaces where people and AI collaborate.

The following examples illustrate this approach.

Note: The competency labels above are English descriptions of the corresponding leadership capabilities. The AI-era behaviors are SmartWorks’ interpretations and do not represent a new competency framework officially established by Zenger Folkman.

Consider two contrasting situations.

A leader may understand AI technology and its business applications but struggle to communicate the purpose of change or gain employees’ trust.

In that case, AI implementation may fail to gain momentum.

Another leader may be highly effective at motivating people and building relationships but lack sufficient understanding of AI’s opportunities and limitations.

That leader may struggle to redesign work effectively.

The challenge is therefore to connect established leadership strengths with the new behaviors required in an AI-enabled workplace.

5. How Can Organizations Measure AI-Era Leadership?

AI usage statistics and reductions in working hours do not necessarily indicate improvements in leadership effectiveness.

A more meaningful question is:

How are leaders influencing the way employees think, make decisions, take initiative, and collaborate?

SmartWorks proposes seven behavioral indicators that organizations can consider alongside established leadership assessments.

1. Reframing Problems

Does the leader question the underlying problem before asking AI to generate solutions?

2. Designing Human–AI Collaboration

Does the leader distinguish appropriately between tasks suited to AI and those requiring human contribution?

3. Exercising Critical Judgment

Does the leader evaluate AI recommendations and make evidence-based decisions?

4. Creating New Value

Does the leader use AI to explore new customer value rather than focusing exclusively on efficiency?

5. Developing People

Does the leader create opportunities for employees to think independently and exercise judgment while using AI?

6. Motivating People Through Change

Does the leader explain the purpose of AI adoption and address employees’ concerns?

7. Encouraging Continuous Learning

Does the leader establish a team environment where experimentation, reflection, and learning from AI-related successes and failures are encouraged?

These seven indicators are proposed by SmartWorks for discussion and development purposes. They are not official assessment items within The Extraordinary Leader™.

By combining insights from EL 360-degree feedback with reflection on AI-related workplace behaviors, organizations can create more targeted leadership development experiences.

6. Using Leadership Strengths to Change Behavior in the AI Era

Consider a hypothetical manufacturing division manager.

The manager’s EL 360-degree feedback indicates a strong capability in Problem Solving and Analysis, while Developing Others receives relatively lower ratings.

The manager enthusiastically introduces AI tools and encourages employees to automate analytical tasks.

After three months, the time required to prepare reports has decreased substantially.

However, a new issue emerges.

Employees increasingly submit AI-generated analyses without explaining their own reasoning or judgments.

The manager might respond by providing additional AI training.

But the more important opportunity may be to change the manager’s own leadership behavior.

When employees present AI-generated analyses, the manager could ask:

“What is your own interpretation of these findings?”

“What evidence supports that conclusion?”

“What alternative explanations should we consider?”

These questions encourage employees to evaluate AI outputs rather than accept them without examination.

The manager can use an existing strength in Problem Solving and Analysis to strengthen the ability to Develop Others.

The objective is not simply to correct weaknesses. It is to leverage existing strengths to create new, more effective leadership behaviors.

This is a hypothetical example developed to illustrate the leadership development approach.

7. Moving Beyond Training to Workplace Behavior Change

Leadership development in the AI era cannot end with classroom learning.

Knowledge must translate into observable changes in workplace behavior.

One possible approach is a three-month learning journey.

Month 1: Redesigning Work

Participants select an existing work process and examine how responsibilities could be redistributed between people and AI.

The objective is to identify opportunities not only for efficiency but also for greater human contribution.

Month 2: Developing Others

Participants practice coaching employees who use AI-generated information.

The emphasis is on helping employees question assumptions, evaluate evidence, and make independent judgments.

Month 3: Championing Change

Participants facilitate discussions about successful and unsuccessful AI applications within their teams.

They use those insights to establish more effective ways of working.

Throughout the three months, participants engage in monthly peer coaching sessions to review their experiences, discuss challenges, and learn from one another.

Instructor feedback and pulse checks can provide additional opportunities to assess behavioral progress.

This approach connects four elements:

360-degree feedback → Strength-based development → Workplace application → Feedback and reflection

Together, these elements can help organizations move beyond AI knowledge acquisition toward meaningful leadership behavior change.

8. What Defines an Extraordinary Leader in the AI Era?

The IT revolution expanded people’s ability to process and share information.

The AI revolution is transforming knowledge work itself by enabling machines to perform aspects of analysis, reasoning, and recommendation.

As a result, the central leadership question is changing.

During the IT revolution, leaders asked:

“How can we use people and technology to improve performance?”

In the AI revolution, they must ask:

“When AI can perform an increasing share of knowledge work, what distinctive value should people create—and how can leaders unlock that potential?”

AI proficiency is becoming an essential leadership capability.

But proficiency alone does not make someone an extraordinary leader.

An extraordinary leader in the AI era is someone who brings out the best in people and combines human capabilities with AI to create value that was previously beyond reach.

The AI revolution does not simply require leaders who know how to delegate tasks to machines.

It requires leaders who use AI to expand human potential.

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References

Jonathan Bowder and Joe Folkman, “AI Leadership Failure: Why AI Transformation Depends on Leaders,” Zenger Folkman, 2026.

The Extraordinary Leader™, Zenger Folkman.

The five AI-era leadership capabilities, seven behavioral indicators, hypothetical example, and suggested leadership development applications presented in this article represent SmartWorks’ analysis and recommendations. They should not be interpreted as an official extension of the Zenger Folkman competency model.