James E. Thorne argues that the AI productivity boom has not yet materialized in full, but this should not be interpreted as evidence that the technology has been overhyped. Instead, he frames the current moment as a buildout phase, suggesting that the transformative economic impact of artificial intelligence is still ahead rather than behind us.
The post pushes back against skeptics who point to the lack of immediate, measurable productivity gains as proof that AI has been oversold. Thorne positions AI adoption as following a familiar pattern where infrastructure and integration must precede the full productivity dividend, implying that patience and continued investment are warranted.
A Morgan Stanley survey of 935 corporate executives across five sectors reveals that AI adoption is driving 11.5% average productivity gains alongside a 4% net reduction in jobs globally. The survey, published in February 2026, focused on industries deemed most exposed to near-term AI impact: consumer staples distribution & retail, real estate, transportation, healthcare equipment & services, and automobiles & components. While U.S. companies actually reported a 2% net gain in jobs, Europe experienced the most significant negative employment effects, and the automotive sector saw the highest net job loss at 10%.
The workforce impact is uneven across company sizes and experience levels. Larger firms (501–1,000 employees) cut 15% of positions, while smaller companies (under 49 employees) saw a 4% net gain. Entry-level employees face the greatest risk of job elimination, while workers with 2–10 years of experience are more likely to be retrained or redeployed. Notably, 27% of employees were retrained in the past 12 months, signaling growing demand for reskilling programs.
For investors, Morgan Stanley highlights that some sectors could achieve savings exceeding 50% of estimated 2026 pre-tax earnings at full AI adoption, with consumer staples, real estate, and transportation potentially surpassing 100% of earnings in benefits. The firm advises investors to reassess AI exposure across portfolios, noting that if AI capabilities continue improving at a non-linear rate, the magnitude of value creation could far exceed current expectations.
