Why You Can't See Your AI Productivity Gains

David Edwards is co-founder and CEO of Kiplot, an AI-native strategic portfolio management platform for enterprise transformation leaders.

While researching our 2026 State of Portfolio report, different transformation leads asked us the same question multiple times: Is everyone else being told to justify why AI hasn’t made them go faster? One of them runs a portfolio of around $250 million with a team of five. She was clear that AI is helping her work faster, and just as clear that she has no spare capacity.

The distance between feeling faster and showing faster is the problem most large organizations will spend the next few years on.

The Productivity Statistics Have Lagged Before

Robert Solow observed in 1987 that the computer age was visible everywhere except in the productivity statistics. Nearly four decades later, in January 2026, a survey of almost 6,000 executives in the U.S., U.K., Germany and Australia found nine in 10 reporting no effect of AI on their own firm’s productivity. Erik Brynjolfsson’s work on the productivity J-curve helps explain why: Getting returns from a new technology means rebuilding the organization around it, which is expensive, slow and invisible on the balance sheet. The firms that rebuilt captured the returns. The ones that just bought the technology did not.

The New Speed Is Absorbed Before It Reaches The Portfolio

That transformation lead is faster at her own work. But the work arriving has grown faster than she has. But the work arriving has grown faster. AI has cut the cost of putting an idea forward. A business case that used to take someone a week now takes an afternoon, and every one of them still lands on her desk needing a proper answer. What has barely moved is the cost of absorbing change. AI has not made legacy integration, regulatory sign-off or retraining thousands of people cheap. A five-person team standing between all of that and a $250 million budget will feel busier, not freer.