How is AI changing the skills for leadership and how should organizations prepare?

Consider two data points that should not coexist: 96% of HR leaders expect entry-level roles to evolve into artificial intelligence (AI) supervision positions within the next five years; yet, 46% still don't proactively offer AI-specific upskilling training.

The destination for work has shifted. However, many organizations still expect their people to navigate there without a map.

The traditional career path was often shaped by technical progression and at times, it could be slow and inequitable. It also produced something that is easy to undervalue until you no longer have it anymore: grounded managers who had done the work, made the mistakes and earned the judgment to lead.

AI is now automating entire categories of tasks – entry-level, routine, high-volume – that once formed the base of the traditional career ladder.

According to new research from Cognizant and Pearson, conducted by Wakefield Research across 750 HR leaders in the United States, the United Kingdom and India, an average of 33% of entry-level tasks are now completed by AI, reaching 39% in the United Kingdom.

Many of these tasks were repetitive and not always equitably distributed. However, they also served a purpose: they gave people space to prove themselves and an opportunity to develop judgment and earn the right to lead over time.

The short-term efficiency gain is real but the longer-term shift is more profound. The traditional ladder is being redefined, disrupting what we have historically valued as experience and creating entirely new pathways to capability, progression and leadership.

The public conversation about AI and the workforce is almost entirely focused on entry-level workers: how to retrain them, protect their jobs and prepare them for new roles. That conversation is necessary but incomplete. The bigger blind spot is at the leadership level necessitating a redesign of the role of leader alongside the roles beneath it.

Yet the data reveals a telling gap: 95% of HR leaders say middle managers are the most crucial factor in ensuring employees use AI effectively and 92% say they are crucial to redefining job roles as AI reshapes day-to-day work. Most organizations are not actively reskilling those managers for what is a fundamentally different position of authority.

This is the real shift. Leaders who built credibility through deep expertise are now operating in an environment where that expertise is increasingly commoditized. The harder transition is not adopting new tools but letting go of the instincts, habits and identity that once defined success and replacing them with the human capabilities that cannot be automated.

That transition, from expert to enabler, from authority to orchestrator, is the one that few organizations are deliberately designing for.

When AI handles more of the technical execution, expertise is no longer enough to anchor leadership. Credibility has to be built elsewhere and 97% of HR leaders agree that human-centred skills are more important than ever in the AI era.

Meanwhile, 64% say organizations now value the ability to identify new problems over the ability to solve existing ones. A particularly notable shift is that 67% say they now value liberal arts degrees, which include interdisciplinary thinking, contextual reasoning and communication, more than they used to.

The new leader is not the person who knows the most. It is the person who can set direction, earn trust and align people and machines around a shared purpose, an orchestrator with a deep foundation of AI fluency.

Connection, judgment in context, the ability to read a room: these are the least tangible skills in most leadership frameworks and they are about to become the most structurally essential. Today's leaders will be the last generation to manage humans alone, which further complicates the transition, as the next generation will be native to it.

The traditional leadership model worked in part because it was invisible. Judgment accumulated over time and institutional knowledge transferred. We learned by doing and progressively earned more responsibility without a designed process but with it gone, the same skills require deliberate and structural instilment.

The report found 94% of HR leaders plan to redefine job roles to reflect how AI is changing day-to-day work. However, redesigning a job description is not the same as redesigning a development pathway. Organizations must move beyond questioning how AI will change the roles performed within it to how AI will alter leadership capabilities and ultimately, what we define as leadership.

The answer lies in redesigning work itself. As AI takes on more of the execution and increasingly contributes to analysis and insight, the goal is not to remove entry-level experience but to transform it into deliberate judgment-building.

Instead of doing every task, individuals guide and challenge the work: setting direction, providing context and owning outcomes. In an AI-enabled organization, leadership is no longer defined by depth of expertise alone but by the ability to create clarity from complexity and enable others to deliver against it.

The next generation of leaders will not be built by preserving old tasks but by redesigning work into development loops, where judgment, context and accountability are what is learned, tested and trusted.

Ninety-four percent of HR leaders believe AI will generate new entry-level roles that do not yet exist. The opportunity to expand access to leadership development is genuine but only if organizations move forward with intention rather than assumption.

If there is no ladder left to climb, the question is not how we rise but whether we build something better in its place – pathways designed for the leaders we actually need, not the system of work we have outgrown.