Most CEOs today will tell you they are serious about AI. They have approved budgets, launched pilots, stood up AI task forces, and explained to their boards how these activities will keep the business from falling behind. What most of them are actually doing, though, is managing an AI portfolio—a collection of experiments, proofs of concept, and incremental productivity tools—rather than leading an AI transformation. These are not the same thing, and the gap between them is widening fast.
There’s plenty of frustration. Bain’s most recent CEO survey finds that roughly 80% of CEOs are unhappy with the pace of their AI transformation programs. But the data tells a sharper story underneath: Around 85% of companies are not executing well. The pace frustration is real, but it is largely a symptom of how the programs are being run, not a reflection of how fast the technology allows them to move.
The emerging leaders are not simply moving faster on the same path; they are operating on a different logic, one that’s rooted in structural divergence. How? By building proprietary intelligence that puts them on a different curve entirely. They have made deliberate, board-level choices about where AI will change the economics of their business. They are rebuilding workflows from the ground up rather than layering AI onto existing processes. They are investing in data, an agentic software capability, and organizational learning as strategic assets. And they are doing all of this with a horizon that extends over years, not the next quarter. READ MORE
By Sarah Elk, Chuck Whitten, Hernan Saenz, Gene Rapoport, Nicolas Bloch, Anne Hoecker, and Pascal Gautheron
Source: bain.com
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