We must train business leaders to manage both people and AI agents
The 21st-century workplace is undergoing a profound transformation. As AI becomes deeply embedded in decision-making, automation and strategy, business leaders must learn to manage both human employees and AI systems. This dual responsibility requires a new approach to executive education that equips leaders with the skills to govern AI while fostering human-centered leadership.
Both of us have dedicated our careers to shaping leadership in a world increasingly influenced by technology. From our different viewpoints and through our experiences working with Fortune 500 companies and in multinational organizations, we have seen the need for a new kind of leadership, where executives understand AI’s capabilities, mitigate its risks, and integrate it ethically into organizational strategy. The rise of hybrid leadership, balancing human intelligence with machine intelligence, is one of the defining challenges of modern business.
The convergence of human and AI management
AI is no longer a distant future. It is the present reality reshaping industries, from financial services and healthcare, to education and governance. AI-driven systems now handle recruitment, risk management, predictive analytics and decision support, raising the question: how should leaders manage teams that include both people and AI?
Humans bring creativity, ethics and emotional intelligence, while AI offers precision, efficiency and automation. The challenge is not whether AI should be adopted, but how leaders can bridge the gap between human and machine intelligence to drive innovation, productivity and ethical decisions.
The rise of hybrid leadership
AI is not just a tool but an adaptive system capable of learning, analyzing and influencing decisions. From HR algorithms screening job candidates to AI-driven financial forecasting, AI increasingly performs tasks traditionally handled by humans.
However, AI lacks intuition, ethical reasoning, and emotional intelligence – qualities that define human leadership. The challenge, then, is preparing for a world where managers must collaborate with AI while maintaining human-centered leadership.
This requires a new breed of leaders who not only understand AI’s mechanics, but also possess the ability to critically evaluate AI insights, mitigate risks and drive responsible AI adoption. Just as managers learn to coach employees, they must now learn to oversee AI systems, ensuring that these tools enhance productivity rather than reinforce systemic flaws or biases.
The role of executive education
Gartner research predicts that by 2026, 75% of organizations will shift from AI pilot projects to full-scale AI operations – and research shows that the companies achieving the highest ROI from AI are those that emphasize human-AI collaboration. Leaders must proactively prepare for this transformation – and executive education must urgently evolve too. Leaders must develop a hybrid skill set comprising eight key areas.
1. AI literacy
- A foundational understanding of AI systems, including machine learning, neural networks and large language models
- Awareness of biases in AI models and the risks of over-reliance on automated decision-making
- The ability to critically assess AI-generated insights and ensure human oversight of crucial decisions
- The ability to ensure AI is used responsibly, transparently, and in compliance with AI-related regulations (such as the EU AI Act and General Data Protection Regulation) and frameworks (such as the OECD AI Principles, IEEE ethics standards, or ISO 42001 standards)
2. Ethical governance
- Development of AI governance frameworks to promote fairness, accountability and transparency
- Mitigation strategies for AI-driven bias that may reinforce discrimination or systemic inequalities
- Policies balancing AI efficiency with ethical considerations such as privacy, security and human autonomy
- Adoption of ethical AI auditing processes and impact assessment, as recommended in the World Economic Forum’s Responsible AI Playbook
3. Change management
- Addressing employee concerns around job displacement and the impact of automation
- Developing upskilling and reskilling programs to support AI-enhanced roles
- Creating a culture of psychological safety where employees embrace AI as an enabler, not a threat. A recent MIT Sloan study found that AI adoption is most successful in companies that actively involve employees in AI strategy, fostering transparency and trust
4. Emotional intelligence
- Strengthening interpersonal skills that AI lacks, such as empathy, active listening, and conflict resolution
- Developing emotional awareness as a superpower for navigating complex team dynamics
- Ensuring that AI aligns with corporate values and stakeholder expectations
5. Strategic thinking
- Anticipating AI-driven disruptions and identifying new market opportunities
- Building adaptive leadership models that account for rapid technological advancements
- Integrating AI into long-term corporate strategy while accounting for regulatory and ethical implications
6. Bridging the human-machine gap
- Understanding AI’s limitations and ensuring human judgment remains central in decision-making
- Creating cross-functional teams that integrate business, ethics and technology experts
- Developing hybrid workflows where AI augments, rather than replaces, human efforts
7. Continuous learning and adaptation
- Embedding lifelong learning as a core leadership principle
- Promoting AI literacy across all levels of leadership
- Incorporating insights from multiple disciplines, including ethics, data science and behavioral psychology, into leadership development
8. Fostering collaboration between humans and AI
- Cultivating a leadership mindset that values AI as a strategic partner rather than a competitor
- Encouraging cross-functional teamwork between technical experts, business leaders, and employees to optimize AI integration
- Designing AI-driven workflows prioritizing human creativity, innovation, and ethical considerations
Investing in AI-ready leadership
Our experience – spanning AI research, policymaking, governance, leadership development and corporate transformation – reinforces the urgent need for leadership programs that prepare executives for the AI era. Global initiatives such as the World Economic Forum’s AI Governance Program and the Partnership on AI are actively shaping responsible AI development, focusing on safety, fairness and accountability.
The organizations that thrive in the AI age will be those that invest in developing AI-literate, ethically-grounded executives, who understand that AI should enhance human capabilities, not replace them – who can orchestrate a symphony of human and machine intelligence.
AI is not just a technological upgrade – it is a fundamental shift in how businesses operate and how leaders must lead. The future of business depends on leadership that balances AI-driven efficiency with human insight, ethics and emotional intelligence.
Sharmla Chetty is CEO of Duke Corporate Education. Professor Tshilidzi Marwala is rector of the United Nations University and UN Under-Secretary-General
