CEOs Question AI’s Productivity Dividend

Thousands of chief executives and senior finance leaders are reporting that artificial intelligence has yet to materially shift employment or productivity, raising board-level questions about returns on rising technology investment. The findings have prompted economists to revisit a decades-old productivity paradox first identified during the early information technology era.

A National Bureau of Economic Research study surveying 6,000 chief executives, chief financial officers and senior executives across the United States, United Kingdom, Germany and Australia found that nearly 90 per cent of firms reported no impact from AI on employment or productivity over the past three years. Although around two-thirds of respondents said they were using AI, average usage amounted to roughly 1.5 hours per week, while a quarter reported no workplace use at all. The results stand in contrast to earnings calls across the S&P 500, where 374 companies referenced AI adoption and largely characterised its impact as positive.

Economists have drawn parallels with Nobel laureate Robert Solow’s observation in 1987 that computers were visible everywhere except in productivity statistics. Apollo chief economist Torsten Slok recently argued that AI remains absent from macroeconomic indicators such as employment, productivity and inflation data. Outside the largest technology groups, he noted little evidence of AI-driven gains in profit margins or earnings expectations.

Academic research presents a mixed picture. A Federal Reserve Bank of St. Louis report found a 1.9 per cent increase in excess cumulative productivity growth since late 2022, while a 2024 MIT study projected a 0.5 per cent productivity uplift over a decade. Despite muted recent outcomes, surveyed executives forecast AI will lift productivity by 1.4 per cent and output by 0.8 per cent over the next three years, alongside a modest 0.7 per cent reduction in employment.

For corporate leaders, the divergence between capital allocation and measurable gains sharpens scrutiny over implementation strategy. Analysts suggest that value creation will depend less on access to AI tools and more on how effectively chief executives integrate them into operating models, workforce planning and competitive positioning.