In 1987, economist and Nobel laureate Robert Solow made a stark statement in regards to the stalling evolution of the knowledge age: Following the arrival of transistors, microprocessors, built-in circuits, and reminiscence chips of the Nineteen Sixties, economists and firms anticipated these new applied sciences to disrupt workplaces and lead to a surge of productiveness. As a substitute, productiveness progress slowed, dropping from 2.9% from 1948 to 1973, to 1.1% after 1973.
New-fangled computer systems have been really, at occasions, producing an excessive amount of data, producing agonizingly detailed stories and printing them on reams of paper. What had promised to be a increase to office productiveness was, for a number of years, a bust. This sudden end result turned often called Solow’s productiveness paradox, due to the economist’s statement of the phenomenon.
“You possibly can see the pc age all over the place however within the productiveness statistics,” Solow wrote in a New York Occasions E-book Evaluation article in 1987.
New knowledge on how C-suite executives are—or aren’t—utilizing AI reveals historical past is repeating itself, complicating the same guarantees economists and Huge Tech founders made in regards to the expertise’s impact on the office and economic system. Regardless of 374 corporations within the S&P 500 mentioning AI in earnings calls—most of which stated the expertise’s implementation within the agency was completely constructive—based on a Monetary Occasions evaluation from September 2024 to 2025, these constructive adoptions aren’t being mirrored in broader productiveness good points.
A research revealed this month by the Nationwide Bureau of Financial Analysis discovered that amongst 6,000 CEOs, chief monetary officers, and different executives from companies who responded to varied enterprise outlook surveys within the U.S., UK, Germany, and Australia, the overwhelming majority see little impact from AI on their operations. Whereas about two-thirds of executives reported utilizing AI, that utilization amounted to solely about 1.5 hours per week, and 25% of respondents reported not utilizing AI within the office in any respect. Almost 90% of companies stated AI has had no impact on employment or productiveness during the last three years, the analysis famous.
Nonetheless, companies’ expectations of AI’s office and financial impact remained substantial: Executives additionally forecasted AI will improve productiveness by 1.4% and improve output by 0.8% over the subsequent three years. Whereas companies anticipated a 0.7% reduce to employment over this time interval, particular person workers surveyed noticed a 0.5% improve in employment.
Solow strikes again
In 2023, MIT researchers claimed AI implementation might improve a employee’s efficiency by practically 40% in comparison with employees who didn’t use the expertise. However rising knowledge failing to point out these promised productiveness good points has led economists to marvel when—or if—AI will provide a return on company investments, which swelled to greater than $250 billion in 2024.
“AI is all over the place besides within the incoming macroeconomic knowledge,” Apollo chief economist Torsten Slok wrote in a latest weblog put up, invoking Solow’s statement from practically 40 years ago. “Right this moment, you don’t see AI within the employment knowledge, productiveness knowledge, or inflation knowledge.”
Slok added that exterior of the Magnificent 7, there are “no indicators of AI in revenue margins or earnings expectations.”
Slok cited a slew of tutorial research on AI and productiveness, portray a contradictory image in regards to the utility of the expertise. Final November, the Federal Reserve Financial institution of St. Louis revealed in its State of Generative AI Adoption report that it noticed a 1.9% improve in extra cumulative productiveness progress for the reason that late-2022 introduction of ChatGPT. A 2024 MIT research, nevertheless, discovered a extra modest 0.5% improve in productiveness over the subsequent decade.
“I don’t assume we must always belittle 0.5% in 10 years. That’s higher than zero,” research creator and Nobel laureate Daron Acemoglu stated on the time. “However it’s just disappointing relative to the guarantees that individuals within the business and in tech journalism are making.”
Different rising analysis can provide the reason why: Workforce options agency ManpowerGroup’s 2026 International Expertise Barometer discovered that throughout practically 14,000 employees in 19 nations, employees’ common AI use elevated 13% in 2025, however confidence within the expertise’s utility plummeted 18%, indicating persistent mistrust within the expertise.
Nickle LaMoreaux, IBM’s chief human assets officer, stated final week the tech large would triple its quantity of younger hires, suggesting that regardless of AI’s potential to automate some of the required duties, displacing entry-level employees would create a dearth of middle-management down the road, endangering the corporate’s management pipeline.
The longer term of AI productiveness
To make certain, this productiveness sample might reverse. The IT increase of the Nineteen Seventies and ‘80s finally gave strategy to a surge of productiveness within the Nineteen Nineties and early 2000s, together with a 1.5% improve in productiveness progress from 1995 to 2005 following a long time of stoop.
Slok noticed the long run impact of AI as doubtlessly resembling a “J-curve” of an preliminary slowdown in efficiency and outcomes, adopted by an exponential surge. He stated whether or not AI’s productiveness good points would comply with this sample would rely on the worth created by AI.
Up to now, AI’s path has already diverged from its IT predecessor. Slok famous within the Eighties, an innovator within the IT house had monopoly pricing energy till opponents might create comparable merchandise. Right this moment, nevertheless, AI instruments are readily accessible as a outcome of “fierce competitors” between massive language model-buildings driving down costs.
Due to this fact, Slok posited, the long run of AI productiveness would rely on corporations’ curiosity in taking benefit of the expertise and persevering with to include it into their workplaces.“In different phrases, from a macro perspective, the worth creation isn’t the product,” Slok stated, “however how generative AI is used and applied in numerous sectors within the economic system.”
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