McKinsey Calls for Redefining Management, Talent in the AI Era

As Generative AI adoption accelerates, most companies have yet to see its financial benefits. Nearly eight in 10 organizations now use generative AI in at least one function, up from 55% a year ago, but more than 80% report no material contribution to their profit and loss. According to McKinsey, companies must refine their operating models and rethink leadership and talent to unlock AI’s true potential.

McKinsey proposes that to succeed in an AI-first world, organizations must evolve from traditional functional models toward “agentic” structures that integrate human and AI systems. This requires redefining management to oversee not just people but also AI agents, and developing talent capable of guiding these systems with both technical understanding and human judgment.

According to McKinsey, the role of the manager is being redefined. As AI systems take on more operational and administrative tasks, managers must become orchestrators who oversee blended systems of people and agents. This involves new forms of literacy including understanding how agentic workflows function, evaluating their performance, and mitigating failures. Leaders must also develop stronger problem-solving and socio-emotional skills to manage hybrid teams effectively.

In the agentic model, leadership accountability expands to include the performance of AI systems. Managers are expected to align AI initiatives with business goals, ensure safe deployment, and integrate automation into decision-making processes. This represents a shift toward managing systems, humans and agents together, where leadership is measured by outcomes and orchestration capability.

The definition of talent is also changing. McKinsey argues that future-ready workforces will depend on individuals who combine deep domain expertise with the ability to collaborate with agentic systems. Generic skills will lose value as AI takes over routine functions, while specialists and generalists who can design and guide AI workflows will gain influence. New roles are emerging across industries, including AI ethics leads, quality assurance managers, and agent coaches.

McKinsey research suggests that 75% of existing jobs will require redesign, upskilling, or redeployment by 2030. The shift, the firm argues, should focus on redefining work rather than eliminating it, preparing talent to supervise, train, and complement agentic systems.

To prepare, McKinsey recommends three immediate actions including redefining job roles to emphasize domain expertise and AI fluency, investing in leadership capability to manage agents responsibly, and mapping how current and emerging roles will evolve. The firm cautions against short-term decisions such as eliminating entry-level roles or replacing skill development with automation without a broader workforce transformation strategy.

McKinsey says that agentic AI represents more than a technological evolution, as it will reshape business models, workflows, and organizational design. Leaders who reimagine management and talent today, the firm says, will be better positioned to capture long-term value as AI continues to redefine how businesses operate.