Economists anticipate that AI will increasingly reshape labor markets in 2026, with some workers potentially experiencing negative impacts before productivity gains translate into higher wages and living standards. Experts like Molly Kinder from the Brookings Institution express concern that employers' stated intention to use AI for efficiency, often aiming to cut labor costs, might lead to significant transformation in the medium to long term, which is currently underestimated.
However, the immediate fears of a widespread "jobs apocalypse" have proven premature. Research by Kinder in partnership with the Yale University Budget Lab found no substantial evidence that generative AI is currently causing widespread job displacement or accelerating occupational shifts beyond historical norms seen with past technological advancements like computers and the internet. A recent rise in graduate unemployment in the US and Europe is attributed more to a broader economic downturn, higher UK payroll taxes, and an oversupply of graduates in the Eurozone, rather than direct AI impacts.
Some studies, particularly from Goldman Sachs and McKinsey, suggest early effects of AI are discernible in specific areas. Goldman's research indicates slower job opening growth since late 2022 in industries highly exposed to AI, such as information and communication services, especially in Germany, Australia, and the US. They found employment in call centers, software publishing, management consulting, and advertising has fallen sharply below historical trends. Goldman also noted that AI-related headwinds are strongest among entry-level workers, with a 10% occupational exposure to AI associated with a 0.1 percentage point drag on annual headcount growth across the broader labor market in France, Canada, and the US, rising to over 0.2 percentage points for entry-level workers in the US and over 0.6 percentage points in Australia.
Conversely, other experts, like Stefano Scarpetta from the OECD and Sir Christopher Pissarides from the London School of Economics, highlight AI's potential to complement workers' skills rather than displace them. OECD research shows small businesses using generative AI did not cut jobs but instead scaled up, became more efficient, and reduced reliance on external consultants. Workers themselves often report satisfaction with AI, as it handles the more tedious aspects of their jobs.
Overall, while some specific groups like freelance graphic designers, copywriters, and junior coding jobs have shown declines in work volumes or hiring, the consensus from labor force surveys is that widespread, AI-driven job displacement across various sectors and countries has not yet occurred. Companies may also attribute layoffs to "AI-readiness" to convey a more positive message to investors, rather than admitting to other negative factors like weak demand or prior over-hiring.
