In 1987, Nobel Prize–winning economist Robert Solow wrote, “You can see the computer age everywhere but in the productivity statistics.”
Gartner projects worldwide AI spending of $2.59 trillion in 2026, a 47% jump over last year, with the US accounting for at least half that amount, according to a wide range of estimates.
But in the US, utilization-adjusted total factor productivity grew just 0.07% over the four quarters ending in the first quarter of 2026. That is a near-standstill by historical standards, far below the roughly half-percent annual pace typical of the pre-ChatGPT decade.
Some 95% of enterprise generative-AI pilots have produced no measurable effect on the bottom line.
A report published this week found that even Meta, one of AI’s loudest boosters, has fallen short in its plan to replace workers with AI.
A working paper posted to SSRN by University of Pittsburgh business professor Mark Ma and colleagues, makes a sweeping claim: The productivity shortfall is caused by employees who resist AI out of fear for their jobs.
Over a five-year period, the researchers looked at millions of Glassdoor reviews, thousands of financial reports, hundreds of AI-investment and layoff announcements by US public companies, and some 10,000 earnings-call transcripts.
They found a wide divide between managers, who tend to be true believers in the promise that AI will deliver sky-high productivity, and employees, who worry that AI-driven productivity gains will cost them their jobs.
Companies, the researchers claim, are caught in a doom loop in which they lay off employees, citing productivity gains. But fear of layoffs causes workers to resist the technology, which sabotages the very gains the companies were counting on. Executives see that lack of productivity and conclude that more layoffs will help. (The flogging will continue until morale improves….)
It’s a tidy narrative. There’s just one problem — while parts of this study are backed by verifiable data, two key elements are not. The report fails to support their assumption that fear of layoffs causes employees to resist using AI, and also that productivity gains would be higher if only workers would enthusiastically embrace it.
The researchers never establish causation in their data. It’s a correlation. (That hasn’t stopped other outlets from reporting the link as causal.)
(A quick aside: One of my favorite podcasters, the economist Tyler Cowen, flagged a study this week that examined 194,631 cross-sectional social science papers and found that the share using causal language in titles or abstracts rose from a stable 20% before 2000 to more than 60% by 2024. Unproven causal claims appear to be something of a fad in social science.)
I don’t buy the claim that employee foot-dragging explains the missing productivity gains, for one simple reason: It makes no sense.
For starters, the notion that rank-and-file employees are broadly resisting AI isn’t entirely true. Many are embracing it. A Columbia Business School survey of 1,400 US employees, written up in Harvard Business Review, found that 31% of individual contributors expressed enthusiasm about adopting AI. And many of the non-enthusiastic are being forced to embrace it. More than half of US workers now use AI.
If AI is a significant driver of productivity, businesses should generally be seeing measurable gains now that roughly half of US workers report using it on the job.
