Five skills every leader needs in the age of AI

As artificial intelligence transforms how organisations operate, leaders are under growing pressure to adapt. Beyond understanding new technologies, they must learn to embed AI into decision-making, team structures, and company culture. A Financial Times analysis revealed that 374 S&P 500 companies mentioned AI in their earnings calls last year, most in positive terms, yet few could point to concrete productivity gains.

Experts say the problem isn’t the technology but leadership alignment. Many organisations fail to link AI to their value propositions or adjust how teams work. Research involving more than 300 board directors shows that fear among employees and poorly designed AI pilots often block progress.

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According to recent academic studies, leading effectively in the age of generative AI requires a new set of competencies. The skills that once defined executive success are no longer enough to navigate the rapid transformation ahead.

Experts say five key skills will determine which leaders succeed in this new era.

1. Span organisational boundaries

AI leadership starts with building diverse networks. Research shows that people connected across industries and professions are more likely to innovate. In Diffusion of Innovations (2003), Everett Rogers explained that technology spreads faster when people observe credible peers using it and understand how it applies to their own work.

For executives, this means engaging with regulators, technologists, startups, and leaders in other sectors. Exposure to different viewpoints helps leaders grasp both the opportunities and risks of AI. In executive classrooms, those who have used AI often guide peers on practical lessons, sharing what works and what does not.

Satya Nadella demonstrated this approach when he became Microsoft’s chief executive. He invited leaders of small tech firms acquired by Microsoft to attend the company’s annual strategic meeting. The result was a broader exchange of ideas that strengthened collaboration and innovation.

Leaders who operate across these boundaries are better positioned to introduce new insights into boardroom discussions and drive informed decision-making.

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2. Redesign organisations

AI creates value only when companies change how they work. Studies have shown that productivity gains depend on new processes, incentives and structures—not the technology alone. Many firms simply attach AI to old workflows and see little improvement.

Leaders must decide when to automate, when to use AI to assist human judgment, and when to keep control in human hands. They also need to focus on building new business models rather than only cutting costs.

At SAP, chief financial officer Dominik Asam has led a major redesign of finance and back-office operations using AI. His team automated routine work, redirected staff towards higher-value tasks, and used data-driven insights to allocate resources more efficiently.

At Russell Reynolds, an executive search firm, managers assign AI “agents” defined tasks while employees handle more complex work. This redesign not only improves productivity but also reshapes organisational culture.

PepsiCo took a similar step by merging its strategy, transformation and technology functions under Athina Kanioura. The move enabled AI to drive process improvement across the business. Leaders who act as organisational architects can turn AI into a source of growth rather than disruption.

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3. Orchestrate team collaboration

AI’s greatest value often emerges in collective decision-making. At Amazon, finance teams now use AI for analysis and forecasting, integrating insights directly into senior meetings. This provides a stronger evidence base for key discussions.

However, effective collaboration requires more than technical use. Studies show that results improve when teams interact with AI iteratively—treating it as a “teammate” rather than a tool. Some experiments even assign AI the role of “devil’s advocate” to challenge group consensus and promote critical thinking.

Leaders must learn to balance human and algorithmic inputs while maintaining psychological safety. Teams should feel comfortable questioning AI outputs and discussing errors. The best leaders act as conductors, ensuring that both people and technology contribute to shared goals.

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4. Coach and develop talent

AI adoption depends on people, not just systems. Workers need guidance, encouragement and space to experiment. Data from millions of managerial job postings in the United States shows a shift away from supervision toward coaching and collaboration.

Jean-Philippe Courtois, who led global sales, marketing and operations at Microsoft, replaced a long-standing inspection culture with one based on coaching. Managers were trained to listen, support learning, and use digital dashboards for real-time feedback. The change freed time for client engagement and made the organisation more adaptive to AI-driven forecasting tools.

As automation handles repetitive tasks, leaders must help employees build new capabilities that complement AI. They must act less as inspectors and more as teachers, ensuring that their teams grow alongside the technology.

Read also: Top 10 fastest-growing AI skills in 2025

5. Lead by example

When asked how leaders can remain relevant in the age of AI, Courtois offered a simple answer: “Use AI every day.”

Donna Morris, Walmart’s chief people officer, follows this advice. She uses AI tools such as ChatGPT when beginning executive searches and for personal tasks like travel planning and research. Her regular use of AI signals to others that experimentation is welcome.

Yet, studies show that many senior leaders speak positively about AI without actually using it. This gap weakens credibility. Leaders who use AI personally build genuine fluency, recognise low-quality outputs, and model curiosity for their teams.

By demonstrating hands-on use, leaders create the social proof that accelerates adoption across their organisations.