Dynamic leadership has become the defining differentiator as companies adopt generative and agentic AI. Top teams that align around a shared purpose, adapt rapidly, and learn continuously are leading the next wave of value creation. This article explores how leadership teams can evolve across five core dimensions to thrive with AI.

What challenges does AI create for executive leadership teams?

Generative AI is a stress test for leadership. While the technology is transforming industries, reshaping customer experiences, and unlocking operational efficiencies, it is also exposing weaknesses in how executive teams function. AI affects every part of the business, and leaders must bring that potential to life. Yet it is common for top executives to find themselves in very different places—some fearful, others excited. To succeed, leadership teams need time to reflect, learn, and collectively build a shared conviction about why AI matters, where it matters most, and how it will change the business.

This is challenging because team members are often more focused on using AI to make their own silos more efficient than on building a collective, AI-enabled ambition.

Leadership teams often spend too much energy reviewing short-term performance or reacting to immediate issues—classic symptoms of recency bias. In doing so, they miss two critical elements: learning from the past and creating the future together.

Those elements are especially critical today as executive teams learn to operate with and through AI. The technology is evolving at such speed that mastery is not an available option. Instead, executives must work with agility—continually learning and adapting.

Historically, the most effective top teams outperform their peers on revenue growth, profitability, and shareholder returns—often because they excel in trust, dissent, cohesion, and judgment.

What makes a top team effective in the AI era?

Leadership excellence has never been about individual brilliance. The best-led companies are distinguished by how their executive leadership teams work together.

Among top teams pursuing AI-enabled transformation, we see senior leaders using AI as a catalyst for faster, more customer-focused, growth-oriented operations. Typically, these teams identify a handful of high-impact areas where small, persistent groups test, learn, and deliver early results—often within 90 days.

For these tests to scale into broader, more permanent change, top teams must share the same vision and urgency. In our experience, the most effective CEOs lead with inquiry rather than directives, asking:

• What would it take to be number one—not just top quartile?
• What’s getting in the way?
• What have we learned this week?

Early results can be uneven, but this discipline of inquiry and evidence builds belief and speed. Over time, transformation becomes less of an initiative and more of a way of working.

Bain’s Top Team Journey framework (see “Teamwork at the Top,” Harvard Business Review, September–October 2024) identifies five key behaviors that define leadership excellence: direction, discipline, collaboration, drive, and dynamism.

Direction: Align around clear strategy and purpose, translating vision into actionable priorities across the organization. Leaders must integrate AI into their strategic vision, balancing short-term efficiencies with long-term transformation.

Discipline: Ensure rigorous execution through consistent decision making that combines AI insights with human judgment and clear accountability.

Collaboration: Build trust and solve complex problems together, aligning technology, data, and business teams around shared priorities.

Drive: Sustain focus and perseverance through complex technological change, maintaining momentum during transformation.

Dynamism: Arguably the most complex behavior. Dynamism requires top teams to lead with foresight while adapting to a world where tomorrow’s rules are being rewritten in real time. It means anticipating and responding to change while maintaining strategic coherence.

What defines dynamic leadership in the AI era?

Dynamic teams react quickly and navigate change with confidence, clarity, and cohesion. They anticipate disruption, embrace it, and translate insight into progress. They ask sharper questions, shift direction without losing alignment, encourage bold thinking, and learn rapidly. Dynamism keeps teams future-oriented without losing their strategic anchor.

Dynamic leadership is built on four interdependent capabilities.

• Inquiry: Seek diverse perspectives, integrate internal and external data, and challenge assumptions.
• Versatility: Adapt roles, workflows, and decisions rapidly and cohesively.
• Innovation: Create space for experimentation and intelligent risk-taking.
• Learning: Turn experience into better team behavior and organizational systems.

Generative AI fundamentally amplifies both the opportunities and the challenges of each element of dynamism. Top teams must integrate quantifiable metrics with human judgment.

How can teams use AI to lead dynamically?

Dynamic leadership is not innate; it can be cultivated. Top teams are learning to use generative AI to strengthen each capability of dynamism.

Inquiry

AI expands what teams can know, but it doesn’t automatically improve how they think. Without thoughtful framing, it can reinforce bias or create false confidence. Inquiry in the gen AI era means cultivating dissent, surfacing hidden risks and assumptions, and integrating frontline human insight with machine intelligence in context. It is about using AI to challenge assumptions—not to validate them.

Versatility

Generative AI enables rapid pivots and real-time decisions. But speed without cohesion creates confusion, friction, and missed opportunities. Versatile teams anchor decisions in shared purpose, define flexible roles, and build regular rhythms for alignment—such as rolling prioritization or monthly strategy resets.

Innovation

AI accelerates ideation, simulation, and testing, but innovation only thrives when psychological safety exists and curiosity is encouraged. Dynamic teams protect time for experimentation—for example, through idea sprints and bounded sandboxes that use real data and real problems while remaining safe to fail and learn. They reward smart risk-taking, explore edge opportunities, and show patience when experiments don’t produce immediate results.

Learning

AI’s rapid feedback generates data. Leadership turns that data into insight. Effective teams convert success and failure into institutional learning through after-action reviews, shared reflection, and updated team norms. Generative AI can detect cross-functional patterns, but it takes leaders to synthesize them into enduring improvement.

What dynamic leadership looks like in action

Generative AI raises the bar for leadership. It is not just about tools—it is about how leadership teams think, align, and adapt. Teams that cultivate direction, discipline, collaboration, drive, and dynamism will be best positioned to lead through disruption. Tools can point to the future. Only cohesive, dynamic teams can choose how to act.

Three high-gain questions leadership teams can ask themselves today:

• Are we aligned on direction, and do we stay unified under pressure?
• How do our team dynamics help or hinder disciplined execution and collaboration?
• Are we fostering true dynamism and a growth mindset in how we lead with AI?

Dynamic leadership doesn’t just adapt to AI—it defines how organizations translate AI’s potential into measurable impact.