AI Productivity Gains Outpace Their Impact on Corporate EBIT

Artificial intelligence is delivering clearer productivity gains for individual workers than for corporate earnings, highlighting the organizational changes companies may need to capture more value from adoption.

An online survey of 1,719 participants in 97 countries found that 80% said AI improved their individual productivity. Only 37% said AI had produced at least some positive impact on organizational earnings before interest and taxes, or EBIT.

The survey was conducted from May 4 to June 8, 2026. Its results show a measurable gap between employee-level gains and company-wide financial performance, without establishing that AI adoption itself is slowing economic growth.

Workflow changes remain limited

About 6% of respondents qualified as AI high performers. The designation applied to respondents who reported at least a 5% EBIT impact and significant value from AI, and the share was unchanged from 2025.

Nearly three-quarters of high performers said their organizations had fundamentally redesigned workflows because of AI. That compared with one-quarter of other respondents.

The difference points to workflow redesign as a feature associated with stronger reported results, although the survey does not establish that redesign caused the higher EBIT impact. AI tools can be deployed before organizations complete the changes needed to capture their value, including employee training, data integration and changes to management practices.

Investment is expected to rise

AI-related operating costs, including token costs, constrained use for about 20% of respondents. Twenty-eight percent said AI represented more than 10% of their enterprise-wide information-technology budget.

Still, 60% expected AI investment to increase over the following year. The figures suggest that companies are continuing to commit resources while facing questions about how quickly those investments will appear in financial results.

Historical U.S. productivity data provides context for the gap between technological adoption and measured productivity. Productivity grew at an average annual rate of 2.8% from 1947 to 1973, compared with 1.3% from 2007 to 2017.

Productivity measures output relative to labor and other inputs. Economists have cited several possible explanations for weaker growth, including digital technologies with less economic impact, delayed benefits from general-purpose technologies, measurement problems and the time required for organizations to restructure.

The current AI pattern is narrower: Workers are reporting improved productivity, while organizational EBIT gains remain limited across the broader respondent base. High performers were more likely to report fundamentally redesigning workflows, and most respondents expected investment to continue rising over the following year.