{"id":483330,"date":"2026-02-18T16:14:19","date_gmt":"2026-02-18T16:14:19","guid":{"rendered":"https:\/\/www.newsbeep.com\/ca\/483330\/"},"modified":"2026-02-18T16:14:19","modified_gmt":"2026-02-18T16:14:19","slug":"thousands-of-executives-arent-seeing-ai-productivity-boom-reminding-economists-of-it-era-paradox","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/ca\/483330\/","title":{"rendered":"Thousands of executives aren’t seeing AI productivity boom, reminding economists of IT-era paradox"},"content":{"rendered":"

In 1987, economist and Nobel laureate Robert Solow made a stark observation about the stalling evolution of the Information Age: Following the advent of transistors, microprocessors, integrated circuits, and memory chips of the 1960s, economists and companies expected these new technologies to disrupt workplaces and result in a surge of productivity. Instead, productivity growth slowed<\/a>, dropping from 2.9% from 1948 to 1973, to 1.1% after 1973.<\/p>\n

Newfangled computers were actually at times producing too much information<\/a>, generating agonizingly detailed reports and printing them on reams of paper. What had promised to be a boom to workplace productivity was for several years a bust. This unexpected outcome became known as Solow\u2019s productivity paradox, thanks to the economist\u2019s observation of the phenomenon.<\/p>\n

\u201cYou can see the computer age everywhere but in the productivity statistics,\u201d Solow wrote in a New York Times Book Review article<\/a> in 1987.<\/p>\n

New data on how C-suite executives are\u2014or aren\u2019t\u2014using AI shows history is repeating itself, complicating the similar promises economists and Big Tech founders made about the technology\u2019s impact on the workplace and economy. Despite 374 companies in the S&P 500 mentioning AI in earnings calls\u2014most of which said the technology\u2019s implementation in the firm was entirely positive\u2014according to a Financial Times analysis<\/a> from September 2024 to 2025, those positive adoptions aren\u2019t being reflected in broader productivity gains.<\/p>\n

A study<\/a> published this month by the National Bureau of Economic Research found that among 6,000 CEOs, chief financial officers, and other executives from firms who responded to various business outlook surveys in the U.S., U.K., Germany, and Australia, the vast majority see little impact from AI on their operations. While about two-thirds of executives reported using AI, that usage amounted to only about 1.5 hours per week, and 25% of respondents reported not using AI in the workplace at all. Nearly 90% of firms said AI has had no impact on employment or productivity over the last three years, the research noted.<\/p>\n

However, firms\u2019 expectations of AI\u2019s workplace and economic impact remained substantial: Executives also forecast AI will increase productivity by 1.4% and increase output by 0.8% over the next three years. While firms expected a 0.7% cut to employment over this time period, individual employees surveyed saw a 0.5% increase in employment.<\/p>\n

Solow strikes back<\/p>\n

In 2023, MIT researchers claimed AI implementation could increase a worker\u2019s performance by nearly 40%<\/a> compared to workers who didn\u2019t use the technology. But emerging data failing to show these promised productivity gains has led economists to wonder when\u2014or if\u2014AI will offer a return on corporate investments, which swelled to more than $250 billion<\/a> in 2024.<\/p>\n

\u201cAI is everywhere except in the incoming macroeconomic data,\u201d Apollo chief economist Torsten Slok wrote in a recent blog post<\/a>, invoking Solow\u2019s observation from nearly 40 years ago. \u201cToday, you don\u2019t see AI in the employment data, productivity data, or inflation data.\u201d<\/p>\n

Slok added that outside of the Magnificent Seven, there are \u201cno signs of AI in profit margins<\/a> or earnings expectations<\/a>.\u201d<\/p>\n

Slok cited a slew of academic studies on AI and productivity, painting a contradictory picture about the utility of the technology. Last November, the Federal Reserve Bank of St. Louis published in its State of Generative AI Adoption report<\/a> that it observed a 1.9% increase in excess cumulative productivity growth since the late-2022 introduction of ChatGPT. A 2024 MIT study<\/a>, however, found a more modest 0.5% increase in productivity over the next decade.<\/p>\n

\u201cI don\u2019t think we should belittle 0.5% in 10 years. That\u2019s better than zero,\u201d study author and Nobel laureate Daron Acemoglu said at the time. \u201cBut it\u2019s just disappointing relative to the promises that people in the industry and in tech journalism are making.\u201d<\/p>\n

Other emerging research can offer reasons why: Workforce solutions firm ManpowerGroup\u2019s 2026 Global Talent Barometer<\/a> found that across nearly 14,000 workers in 19 countries, workers\u2019 regular AI use increased 13% in 2025, but confidence in the technology\u2019s utility plummeted 18%, indicating persistent distrust.<\/p>\n

Nickle LaMoreaux, IBM\u2019s chief human resources officer, said last week the tech giant would triple its number of young hires<\/a>, suggesting that despite AI\u2019s ability to automate some of the required tasks, displacing entry-level workers would create a dearth of middle managers down the line, endangering the company\u2019s leadership pipeline.<\/p>\n

The future of AI productivity<\/p>\n

To be sure, this productivity pattern could reverse. The IT boom of the 1970s and \u201980s eventually gave way to a surge of productivity in the 1990s and early 2000s, including a 1.5% increase in productivity growth<\/a> from 1995 to 2005 following decades of slump.\u00a0<\/p>\n

Economist and Stanford University\u2019s Digital Economy Lab director Erik Brynjolfsson noted in a Financial Times op-ed<\/a> the trend may already be reversing<\/a>. He observed that fourth-quarter GDP was tracking up 3.7%, despite last week\u2019s jobs report revising down job gains to just 181,000, suggesting a productivity surge. His own analysis indicated a U.S. productivity jump of 2.7% last year, which he attributed to a transition from AI investment to reaping the benefits of the technology. Former Pimco CEO and economist Mohamed El-Erian also noted job growth and GDP growth continuing to decouple<\/a> as a result in part of continued AI adoption, a similar phenomenon that occurred in the 1990s with office automation.<\/p>\n

Slok similarly saw the future impact of AI as potentially resembling a \u201cJ-curve\u201d of an initial slowdown in performance and results, followed by an exponential surge. He said whether AI\u2019s productivity gains would follow this pattern would depend on the value created by AI.\u00a0<\/p>\n

So far, AI\u2019s path has already diverged from its IT predecessor. Slok noted in the 1980s, an innovator in the IT space had monopoly pricing power until competitors could create similar products. Today, however, AI tools are readily accessible as a result of \u201cfierce competition\u201d between large language model-buildings driving down prices.<\/p>\n

Therefore, Slok posited, the future of AI productivity would depend on companies\u2019 interest in taking advantage of the technology and continuing to incorporate it into their workplaces. \u201cIn other words, from a macro perspective, the value creation is not the product,\u201d Slok said, \u201cbut how generative AI is used and implemented in different sectors in the economy.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"In 1987, economist and Nobel laureate Robert Solow made a stark observation about the stalling evolution of the…\n","protected":false},"author":2,"featured_media":483331,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[62,276,277,49,48,85487,149,61,21982],"class_list":{"0":"post-483330","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-artificial-intelligence","10":"tag-artificialintelligence","11":"tag-ca","12":"tag-canada","13":"tag-economic-data","14":"tag-productivity","15":"tag-technology","16":"tag-the-future-of-work"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/posts\/483330","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/comments?post=483330"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/posts\/483330\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/media\/483331"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/media?parent=483330"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/categories?post=483330"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/tags?post=483330"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}