Accelerating AI-Related Job Losses Through May 2026

The evidence shows a clear acceleration in AI-attributed job cuts, with AI becoming the single leading reason companies cite for layoffs.

• May 2026: highest May layoffs since 2020. U.S. employers announced slightly over 97,000 job cuts in May 2026 — the highest May total since the onset of COVID-19. AI was the leading reason cited for the third straight month, accounting for roughly 40% of all cuts .
• AI as #1 layoff driver. In April 2026, AI accounted for 21,490 cuts, or 26% of the 88,387 total, making it the top reason for the second consecutive month . In May, AI remained the leading factor .
• Year-over-year surge. Total AI-attributed job cuts in the U.S. surged from ~12,700 in 2024 to ~54,800 in 2025, with thousands more recorded in early 2026 .
• CFO projections. A March 2026 Duke/NBER survey of 750 CFOs projected a sharp acceleration in AI-driven headcount reduction — potentially a 9× increase by 2027 .

Robert Shiller's Warning: Fear Itself as an Economic Trigger

Nobel laureate Robert Shiller published a guest essay in The New York Times on June 22, 2026, titled "We Have to Stop Freaking Out About A.I." . His argument:

• The danger is narrative-driven. Shiller argues the biggest risk is not AI technology itself, but the "potency of the fear it is generating." When widespread anxiety becomes the dominant economic narrative, it can alter real behavior — consumers pull back spending, companies freeze hiring — creating a downturn that was not technologically necessary .
• "Depressions, formerly called panics." Shiller draws on his work in Narrative Economics, noting that economic depressions have historically been driven by panics and contagious stories. He warns the current AI-job-destruction narrative is behaving exactly like those historic panic stories .
• 70% of Americans expect AI to reduce jobs. Shiller cites a March 2026 Quinnipiac University poll in which 70% of Americans said they believe AI will reduce the number of jobs. A June 2026 Pew survey found only 16% expect AI to have a positive effect on society over the next 20 years .
• Self-fulfilling prophecy mechanism. If enough people believe AI will destroy jobs, they cut spending and delay major purchases. Companies, expecting lower demand and fearing automation, slow hiring or accelerate layoffs — which then confirms the original fear . Shiller warns this "doommaxxing" could trigger a recession even if AI's actual displacement effect is modest .

Synthesis: The Three-Layer Risk

Bottom line: Fitch has positioned AI-driven job displacement as an emerging credit risk concentrated in TMT and private credit, supported by hard data showing AI-attributed U.S. layoffs rising sharply through May 2026. Shiller's warning adds a distinct second-order risk: the prevailing fear narrative itself may suppress aggregate demand enough to trigger a downturn, independent of AI's actual technical capabilities.

Accelerating AI-Related Job Losses Through May 2026

The evidence shows a clear acceleration in AI-attributed job cuts, with AI becoming the single leading reason companies cite for layoffs.

• May 2026: highest May layoffs since 2020. U.S. employers announced slightly over 97,000 job cuts in May 2026 — the highest May total since the onset of COVID-19. AI was the leading reason cited for the third straight month, accounting for roughly 40% of all cuts .
• AI as #1 layoff driver. In April 2026, AI accounted for 21,490 cuts, or 26% of the 88,387 total, making it the top reason for the second consecutive month . In May, AI remained the leading factor .
• Year-over-year surge. Total AI-attributed job cuts in the U.S. surged from ~12,700 in 2024 to ~54,800 in 2025, with thousands more recorded in early 2026 .
• CFO projections. A March 2026 Duke/NBER survey of 750 CFOs projected a sharp acceleration in AI-driven headcount reduction — potentially a 9× increase by 2027 .

Robert Shiller's Warning: Fear Itself as an Economic Trigger

Nobel laureate Robert Shiller published a guest essay in The New York Times on June 22, 2026, titled "We Have to Stop Freaking Out About A.I." . His argument:

• The danger is narrative-driven. Shiller argues the biggest risk is not AI technology itself, but the "potency of the fear it is generating." When widespread anxiety becomes the dominant economic narrative, it can alter real behavior — consumers pull back spending, companies freeze hiring — creating a downturn that was not technologically necessary .
• "Depressions, formerly called panics." Shiller draws on his work in Narrative Economics, noting that economic depressions have historically been driven by panics and contagious stories. He warns the current AI-job-destruction narrative is behaving exactly like those historic panic stories .
• 70% of Americans expect AI to reduce jobs. Shiller cites a March 2026 Quinnipiac University poll in which 70% of Americans said they believe AI will reduce the number of jobs. A June 2026 Pew survey found only 16% expect AI to have a positive effect on society over the next 20 years .
• Self-fulfilling prophecy mechanism. If enough people believe AI will destroy jobs, they cut spending and delay major purchases. Companies, expecting lower demand and fearing automation, slow hiring or accelerate layoffs — which then confirms the original fear . Shiller warns this "doommaxxing" could trigger a recession even if AI's actual displacement effect is modest .

Synthesis: The Three-Layer Risk

Bottom line: Fitch has positioned AI-driven job displacement as an emerging credit risk concentrated in TMT and private credit, supported by hard data showing AI-attributed U.S. layoffs rising sharply through May 2026. Shiller's warning adds a distinct second-order risk: the prevailing fear narrative itself may suppress aggregate demand enough to trigger a downturn, independent of AI's actual technical capabilities.