AI at the Apex: Evolving Leadership and Talent Management

Generative and agentic AI are transforming leadership, talent strategy, and organisational design. Explore what this means for UK senior leaders.

By Richard Waddell

AI’s evolution is accelerating, but for UK senior business leaders, the conversation has moved far beyond automation and process improvement.

The emergence of generative AI (gen AI) and the first agentic AI systems is fundamentally reshaping the nature of leadership, talent strategy, and organisational design at the highest levels.

From Generative to Agentic: A New Leadership Paradigm

Generative AI - typified by models like OpenAI’s GPT-4 and Google’s Gemini - has already transformed how leaders access insight, scenario plan, and communicate. These systems can synthesise market intelligence, draft board papers and even simulate stakeholder responses, compressing hours of executive work into minutes. McKinsey’s 2024 report notes that over half of C-level executives in the UK now use gen AI tools weekly, not just for efficiency but as strategic thought partners (McKinsey, 2024).

The next frontier is agentic AI: systems capable of autonomous goal-setting, decision-making, and complex multi-step execution. While still nascent, agentic AI is being piloted by global leaders such as DeepMind (London-based and now part of Google) and in industrial settings by Siemens and Rolls-Royce, where AI agents optimise supply chains and maintenance schedules with minimal human intervention (Siemens AI Labs).

For leaders, this means a shift from directing action to orchestrating ecosystems - where AI is not just a tool, but a semi-autonomous collaborator.

Strategic Talent Implications: Beyond the Basics

This new landscape demands a radical rethink of leadership and talent management, for example:

Selection and Assessment: Gen AI is already being used by Unilever and HSBC to assess leadership candidates through AI-driven video interviews and psychometric analysis, reducing bias and surfacing non-obvious talent. However, agentic AI will soon require leaders who can manage not just people, but AI agents - evaluating their performance, ethics and alignment with organisational values.
Onboarding and Development: AstraZeneca has integrated gen AI into onboarding, providing new leaders with dynamic, context-aware knowledge bases and scenario simulations. In private equity, firms are using AI to better understand leadership capability and manage talent across portfolio companies.
Succession and Workforce Planning: Rolls-Royce leverages AI to model succession scenarios, factoring in not only human capability but also the evolving roles of AI agents in critical functions. This hybrid workforce planning is becoming essential as agentic systems take on more responsibility.

There are numerous sector-specific examples as well:

Retail: The John Lewis Partnership has piloted gen AI to support board-level scenario planning, helping family and non-family directors navigate succession and governance in an era where digital and human capital are equally important.
Industrials: Siemens’ use of agentic AI in predictive maintenance and supply chain orchestration is redefining what leadership means in operationally intensive environments.
Private Equity: Hg Capital, a leading UK tech investor, has embedded AI into its due diligence and post-deal value creation, assessing, for example, the AI maturity of target firms.
Healthcare and Life Sciences: The NHS AI Lab is pioneering agentic systems for resource allocation and patient flow, requiring clinical and operational leaders to collaborate with AI in real-time decision environments.

Risks and Boardroom Imperatives

With these advances come new risks. Agentic AI introduces questions of accountability, transparency, and trust. The UK’s AI Security Institute, launched in 2024, is already advising boards on governance frameworks for AI agents, emphasising the need for robust oversight and ethical guardrails (UK AI Security Institute).

Leaders must also grapple with the “black box” problem: as AI systems become more autonomous, understanding their decision logic becomes harder. This is especially acute in regulated sectors like healthcare and finance, where explainability is not optional. The Financial Conduct Authority’s recent guidance on AI governance is essential reading for boards (FCA Corporate AI Update).

Actionable Priorities for Senior Leaders

Develop AI fluency at board and executive level: Move beyond awareness to hands-on engagement with gen AI and agentic tools. Consider reverse mentoring and dedicated board sessions on AI ethics and governance.
Redesign capability assessment: Incorporate AI literacy, adaptability and the ability to lead hybrid human-AI teams into selection and succession criteria.
Invest in explainability and ethics: Partner with technical experts to ensure AI systems are transparent and aligned with organisational values.
Build a culture of experimentation: Encourage leaders to pilot agentic AI in controlled environments, learning from both successes and failures.
Engage with external ecosystems: Build relationships with AI labs, regulators and peer organisations to stay ahead of emerging risks and opportunities.

Conclusion: Orchestrating the Future

For UK senior leaders, the challenge is not whether to adopt AI, but how to lead confidently and ethically alongside increasingly autonomous systems.

Generative and agentic AI are redefining leadership, decision-making, and organisational culture, demanding a shift from managing tools to partnering with intelligent collaborators.

Success will belong to those who can balance innovation with stewardship, embedding AI fluency and ethical governance into the boardroom and throughout their organisation. This means investing in ongoing learning for leaders, redesigning succession and assessment to include the ability to lead hybrid human-AI teams and fostering a culture of transparency and psychological safety.

As AI systems assume greater responsibility, open dialogue about risks and limitations is essential to maintain trust and alignment with organisational values. Leaders must also engage with external stakeholders - regulators, technology partners, and peers - to shape responsible AI practices across the sector.

Ultimately, the future will favour leaders who combine strategic vision, technical fluency, ethical rigour and human empathy. By doing so, they will not only navigate the complexities of the AI era but also unlock new value and resilience for their organisations and society.

To find out more about Boyden’s leadership consulting solutions and how we can help you to select, onboard and develop senior talent in your business, contact Richard Waddell, Managing Partner Leadership Consulting.

About the Author

Richard Waddell

Managing Partner, Leadership Consulting, United Kingdom

Richard Waddell brings two decades of experience in leadership consulting, focusing on leadership assessment, development, team performance and succession planning. With a background in the British Army and as a human capital consultant, Richard provides clients across diverse sectors with insights and actionable ideas to maximise leadership performance and develop high-performing teams.