Which companies are cutting jobs because of AI, which careers are safe, and what you can do. Government automation is part of the story too — from DOGE's federal cuts to agencies adopting tools like Anthropic's Claude. Tracking 4 documented layoff events.
| Date | Company | Industry | Jobs Cut | State | AI Cause |
|---|---|---|---|---|---|
| Mar 20, 2026 | Morgan Stanley eFinancialCareers ↗ | Finance | — | NY | Morgan Stanley cut jobs in early 2026 alongside Goldman Sachs and Bank of America as Wall Street banks accelerated AI deployment in trading, operations, and client services. Bank executives described AI as enabling them to do more work with fewer staff, with JPMorgan CEO Jamie Dimon explicitly stating he would 'definitely eliminate some jobs' due to AI. |
| Mar 15, 2026 | Goldman Sachs Bloomberg ↗ | Finance | — | NY | Goldman Sachs President and COO described the firm's traditional operations as a 'human assembly line ripe for automation,' signaling AI-driven role reductions in back-office and operations functions. Goldman and other Wall Street banks cut jobs in cycles throughout 2026 as AI was introduced across trading, risk management, wealth management analytics, and client services. |
| Jan 15, 2026 | Vox Media Press Gazette ↗ | Media | — | NY | Vox Media made editorial cuts in early 2026 as part of the broader journalism layoff wave. AI Overviews and AI-synthesized content had measurably reduced click-through rates from Google Search to digital news outlets, eroding advertising revenue and the business case for prior staffing levels. |
| Nov 01, 2025 | IBM CIO Dive ↗ | Tech | — | NY | IBM confirmed in Q4 2025 that AI agents had already replaced hundreds of back-office roles and announced additional cuts as it shifted talent toward AI and quantum computing. IBM had previously stated in 2023 that it would pause hiring for ~8,000 back-office roles that could be performed by AI. By late 2025, the HR and accounting automation had been implemented, with confirmed reductions in those functions. |
The industries most at risk include customer service, content creation, entry-level software QA, data processing, and certain financial and legal research roles — wherever routine, rules-based tasks can be automated. Physical trades, healthcare, and work requiring social judgment and physical dexterity remain significantly more resistant.
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