What is Leadership in the Age of AI?

The advent of artificial intelligence is reshaping the landscape of leadership. Some things don't change (the Why of leadership), but others (the How) might, at least partially. For one, we know we need leadership now - the magnitude of inflection is as large as any we have seen.

In this post, I riff on some of the discussions hosted by Amir Ouki , where Tami Craig Schilling Tiger Tyagarajan Martin Reeves and I had recently as part of the Autonomous Innovation Summit organized by Philippe De Ridder , who leads the Board of Innovation.

We explored perspectives on what it takes to be a great leader in the age of AI, the surprising shifts in decision-making processes, and the emerging hybrid models that blend human judgment with machine efficiency.

In my view, the federating concept in all of this is that leadership has always been about managing, for all practical intent and purpose, somewhat autonomous systems through "high-leverage points." Unlike management, which often speaks the language of process and psychology, leadership speaks the language of systems dynamics, politics, and social psychology. CEOs don't have a button to press to lead companies; they influence them through leverage points such as incentives, culture, and strategy. How does that change now that these companies will be increasingly bionic, with humans and machines collaborating and influencing each other in networks?

Here's a short rundown.

1. The New Qualities of Leadership: Experimentation and Exploration

Experimentation and Risk-Taking

One clear insight from our discussion is the premium placed on experimentation. Leaders today are expected to:

• Take calculated risks: Experimenting with new ideas is no longer a long-term gamble that spans years—it’s a rapid-cycle process where quick iterations can reveal what works and what doesn’t.
• Redefine risk: In the AI era, “risk” means embracing uncertainty with the understanding that failure is a fast and valuable feedback mechanism. Instead of waiting years and spending vast sums to test an idea, AI can accelerate the cycle of learning.

Exploration: Asking the Right Questions

The ability to explore uncharted territories is crucial:

• Ask questions instead of just providing answers: With AI platforms like ChatGPT readily available to generate answers, the true differentiator is the leader who can ask insightful, probing questions that spark innovation.
• Pioneering partnerships: True leadership means venturing into areas no one else has and collaborating with unexpected partners. This form of exploration leverages AI’s capability to process and learn from vast datasets, while human creativity maps out the unexplored.

Surprising Insight: While technology provides answers at scale, it is the human talent for asking the right questions and connecting disparate dots that will set tomorrow’s leaders apart.

2. The Hybrid Decision-Making Model: Human-AI Collaboration

Beyond the Binary: Rejecting Extremes

The conversation highlights a crucial prediction: rather than a full handover to AI (the “werewolf model”) or complete human autonomy, the future will be hybrid:

• Cyborg Decision Making: The optimal approach is a balanced model where AI handles routine, data-intensive tasks, and human leaders focus on creativity, strategy, and ethical judgment.
• Maintaining human involvement: Leaders must avoid the trap of letting technology override human insight. Just as pilots must keep their skills sharp despite advanced autopilot systems, leaders must “keep their hands dirty” by engaging directly with customers, teams, and the ever-changing business landscape.

Building System Architectures for Hybrid Decision Making

Effective leadership in this new era involves designing organizational systems that:

• Incorporate both AI insights and human intuition.
• Develop infrastructures for continuous learning, collaboration, and knowledge management.
• Foster agile cultures where decision making is distributed across multiple levels and informed by both data-driven insights and human judgment.

Surprising Insight: The real competitive advantage won’t come from having access to the most powerful algorithms—it will be determined by how well leaders can integrate those algorithms into a system that amplifies human ingenuity.

3. Four Leverage Points for AI-Enhanced Organizations

Several leaders emphasized a framework where effective leadership harnesses AI to impact four critical areas:

1. Network Topology

• Mapping skills and resources: Understand where the talents lie—both human and machine. That's where the intelligence is, and what influences the behavior of the system.

2. Learning Infrastructures for Long-Term Thinking

• System Two Thinking: Develop processes that enable teams to tackle uncertainty and plan for long-term challenges, mirroring the cognitive shift from fast, reactive decisions to more deliberate, reflective ones.
• Amplifying learning: Use AI to continuously assess and optimize the distribution of skills across the organization.

3. Enablement and Knowledge Management

• Beyond traditional methods: Leverage AI to capture, manage, and disseminate knowledge more effectively than ever before.
• Learning organizations: Harvest teachable moments from daily operations, that are integrated into the daily flow of work, ensuring that lessons are retained and applied.

4. Collaboration Infrastructures

• Building the “synaptic” structure: Just as the brain relies on complex synaptic connections for higher function, organizations need robust collaboration tools, practices, and culture - among others - that foster innovation across all levels.

Surprising Insight: The inimitability of a system that blends AI with human networks may well become the ultimate source of sustainable competitive advantage—one that is far harder for competitors to replicate than any single technology or algorithm.

4. The Evolving Role of Skills: Beyond STEM

While technical skills in math, computer science, and algorithm development remain essential, the conversation reveals an equally critical, and sometimes overlooked, set of competencies:

• The Art of Questioning: In a world where the algorithmic answers are readily available, the power lies in asking the right questions.
• Interpersonal Relationships and Trust: As AI commoditizes technical knowledge, the human capacity to build trust and foster meaningful relationships will become a unique differentiator.
• Holistic Problem Solving: Leaders must connect the dots across disciplines, using insights from social sciences, history, and human behavior to guide strategy and decision making.

Surprising Insight: As technology levels the playing field on many technical fronts, the unique human elements—creativity, ethical judgment, and interpersonal trust—will rise in prominence, making them indispensable leadership qualities.

5. Overcoming Pitfalls: Function vs. Competitive Advantage

Leaders must navigate several potential pitfalls as they integrate AI into their organizations:

Functional Impact vs. Competitive Advantage

• Temporary vs. sustainable gains: While early adopters may see short-term benefits from using AI, these advantages can quickly vanish if competitors gain access to the same technology.
• The real advantage: It lies not in the technology itself, but in creating a system that is uniquely inimitable. This might include: Complexity and path dependency: Systems built over time, with interwoven processes and cultural elements, are hard to replicate. Unique organizational culture: A strong, well-defined culture is perhaps the most elusive yet powerful asset a company can cultivate.

Surprising Insight: The greatest challenge is not mastering the AI tool but designing an ecosystem that leverages that tool in a way that competitors cannot easily duplicate. The focus must be on integrating human systems and technology to create long-term, sustainable value.

Conclusion: A Call to Adaptive, Hybrid Leadership

As AI becomes as ubiquitous as a calculator or a spreadsheet, the true competitive edge will come from our ability to use it thoughtfully, integrate it seamlessly with human judgment, and nurture the relationships and culture that technology alone cannot replicate. This is about management and organization design as much as technology.

In the age of AI, leadership is not about surrendering to technology but about harnessing it to amplify the best of what humans can do. The new leader is an experimenter, an explorer, and a system architect—someone who asks the right questions, builds resilient hybrid decision-making frameworks, and creates inimitable systems of innovation and collaboration. And one last thing: leaders, ask good questions of your organizations, and its AI. That's one thing that, for now, humans do much better than machines.

This essay is part of a series on AI-augmented Collective Intelligence and the organizational, process, and skill infrastructure design that delivers the best performance for today's organizations. More here. Get in touch if you want these capabilities to augment your organization's collective intelligence.