In 1987, the Nobel laureate economist Robert Solow famously observed, “You can see the computer age everywhere but in the productivity statistics.” Nearly four decades later, AI has produced a version of its own. Call it the abundance paradox.

At the level of the individual worker, the evidence of AI-driven abundance is easy to see. Researchers found that AI typically raises productivity on specific tasks 15% to 30% in real-world work settings, and 20% to 60% in controlled studies. Meanwhile, 8 in 10 professionals say AI has made them more productive at work, according to McKinsey’s 2026 State of AI survey of more than 1,700 respondents in 97 countries.

At the level of the company, however, the picture looks very different. Only 37% of McKinsey’s respondents can link AI to any impact on their organization’s earnings before interest and taxes, or EBIT—essentially unchanged from a year earlier.

Relatedly, the National Bureau of Economic Research reports that although 69% of firms were using AI, 89% of executives reported no impact on productivity over the previous three years. And PwC’s 2026 Global CEO Survey of more than 4,400 chief executives in 95 countries found that 56% had seen AI deliver neither higher revenue nor lower costs in the past year.

The gains individuals get from AI are not adding up to gains for the companies they work for. Closing this gap is now one of the most important tasks facing business leaders. Here’s how to do it.

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