AI is turning workers into superhumans. Their leadership teams haven’t kept up

On the ground, AI is already delivering. Engineers are shipping code faster, customer service teams are resolving tickets in half the time, and operations teams are automating workflows that used to require approval from three departments. Workers equipped with AI tools are operating at speeds and scales that would have seemed impossible two years ago.

At the top, it’s a different story. The same C-suites championing AI transformation in earnings calls are the ones slowing it down in practice. Sequential sign-offs. Functional silos. Decisions that get reopened after they’ve been settled. Leadership teams designed for a slower, more predictable era are now the primary constraint on the transformation they claim to be leading.

Here’s the uncomfortable truth: AI can’t fix a broken C-suite running on an antiquated operating system. 

Why Most C-Suites Can’t Get Out of Their Own Way

In the Conference Board’s 2026 annual leadership survey, CEOs ranked investing in AI and building AI expertise as their top priorities. Boards are demanding efficiency gains. Investors reward headcount reductions tied to automation. But while the pressure to move increases, most leadership teams are stuck answering the wrong questions.

Some are treating AI as a functional project — a tech deployment led by a transformation office. Others frame it as a change management exercise run by the Chief People Officer, narrowing the conversation to talent acquisition and reskilling.

Each of these approaches produces real gains. Pilots can generate efficiency and can even be built out at scale. Transformation offices can attract great talent and provide governance and oversight. Change management discussions surface important workforce questions.

But none of this addresses the real bottleneck: the C-suite itself. A transformation office cannot, on its own, change how the executive team makes decisions, shares information, resolves trade-offs, or holds itself accountable. And transformation won’t succeed if it starts from a single operational function under one executive.

Boardroom conversations sound like transformation. Execution looks like incremental optimization: doing the same things faster, with fewer people, at marginally lower cost. That’s what gets measured — and that’s what analysts reward in earnings calls.

The actual bottleneck isn’t the technology. It’s the leadership team that refuses to operate any differently than it did five years ago.

The Dysfunction Most Leaders Won’t Name

“Every member of the C-suite now needs to be able to think and operate at the enterprise level, not just as the leader of a BU or function. But most leadership teams were not built or trained that way. If the operating model at the top does not evolve to support faster, more integrated enterprise decision-making, the market, the technology, or the organization will eventually force the issue.”

— Carolyn Dewar, co-author, A CEO for All Seasons: Mastering the Cycles of Leadership

The traditional C-suite model was designed for a different era. Reporting structures were vertical. Each executive owned a lane. Contribution to enterprise decisions was filtered through a functional lens. Executive meetings were primarily information exchanges: here’s what’s happening in my domain. The purpose was coordination and consensus.

This worked well when change moved slowly enough to stay within functional boundaries. AI doesn’t do that. AI-led change flows horizontally, touching every function simultaneously. A decision about how AI will process supplier invoices is also a decision about finance controls, legal........

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