OpenAI CEO Sam Altman has publicly accused some companies of using artificial intelligence as a convenient cover story for job cuts that were already in the pipeline — a practice he and others are calling “AI washing.”
Speaking at the India AI Impact Summit 2026 in New Delhi, Altman sat down with CNBC-TV18 and pushed back against the widely circulated idea that AI is the primary force driving mass layoffs sweeping the global economy. His comments draw a sharp line between organizations genuinely restructuring around the technology and those using it as a headline-friendly excuse to cut costs.
What “AI Washing” Actually Means
At its core, AI washing describes the practice of companies framing job cuts as an unavoidable response to AI-driven transformation — when the real causes are more ordinary, such as overhiring, weakening revenues, or cost-reduction targets. The term borrows from “greenwashing,” where organizations exaggerate their environmental credentials to improve their public image.
Altman was candid but measured. “I don’t know what the exact percentage is, but there’s some AI washing where people are blaming AI for layoffs that they would otherwise do,” he said. He was equally clear that genuine AI-driven displacement is also happening, adding, “There’s some real displacement by AI of different kinds of jobs.”
The Numbers Tell a Different Story
Cold hard data puts the scale of AI-linked job losses in perspective. Consulting firm Challenger, Gray & Christmas tracked roughly 55,000 layoffs directly attributed to AI during 2025 — a significant figure in isolation, but one that amounts to less than 1% of total job losses recorded that year.
A study from the National Bureau of Economic Research reinforced that picture. Researchers surveyed thousands of C-suite executives across the United States, United Kingdom, Germany, and Australia, and found that nearly 90% reported AI had no impact on workplace employment during the three years following the late-2022 release of ChatGPT.
The Yale Budget Lab reached a similar conclusion. Analyzing Bureau of Labor Statistics data through November 2025, researchers found no meaningful shifts in employment patterns for workers in roles with high AI exposure — adding another layer of evidence that mass AI-driven displacement hasn’t materialized at scale just yet.
Earlier this year, Oxford Economics released a report concluding that the majority of layoffs are being driven by familiar factors — overstaffing and poor financial results — far more than by AI. The firm went further, suggesting that some companies are deliberately framing conventional cost cuts in AI language to make routine downsizing sound like forward-thinking transformation. A separate January report from Morgan Stanley echoed that concern, finding that businesses are increasingly treating AI as a “license to reduce headcount.”
The Amazon Example
Amazon provides one of the most striking illustrations of what AI washing can look like in practice. The company cut 14,000 jobs and told employees at the time that rolling out AI meant it would “need fewer people doing some of the jobs that are being done today.” Months later, the company reversed course and stated that AI was not actually the reason for those cuts — a reversal that raised pointed questions about how the original messaging was framed.
Other major corporations — including IBM, Salesforce, and HP — have also cited AI as a factor in reducing their workforces. It is worth noting, however, that no evidence of AI washing has been formally established at those companies specifically.
New Jobs vs. Displacement: An Unresolved Debate
Altman did not dismiss the long-term threat AI poses to employment. He acknowledged that real job displacement is happening and will grow. “We’ll find new kinds of jobs, as we do with every tech revolution,” he said, “but I would expect that the real impact of AI doing jobs in the next few years will begin to be palpable.”
Research firm Forrester has projected that around 10 million jobs globally could be lost as enterprise AI adoption accelerates, while also forecasting that new roles will emerge over time to take their place. Gartner’s analysis suggests roughly 32 million jobs will be “reconfigured, redesigned, or fused” annually from 2028 onward. Gartner analyst Helen Poitevin put the reskilling challenge in stark terms, estimating that roughly 150,000 workers would need to be upskilled every single day in the years ahead — a pace she described as “jobs chaos,” though not an outright apocalypse.
Industry Leaders Sharply Divided
Not every tech executive shares Altman’s measured tone. Anthropic CEO Dario Amodei has warned that AI could eliminate up to 50% of entry-level white-collar jobs within five years. Microsoft AI CEO Mustafa Suleyman went further, telling the Financial Times that most professional white-collar tasks — from legal work to accounting to project management — could be fully automated within 12 to 18 months. Google DeepMind CEO Demis Hassabis also said he is already noticing an AI-driven slowdown in junior-level hiring at his company.
Stanford economist Erik Brynjolfsson offered a more data-grounded perspective, pointing to a 2.7% year-over-year productivity increase last year alongside a 13% relative decline in employment among early-career workers in AI-exposed roles — signs, he argued, that AI’s economic effects are beginning to surface in the numbers.
What Altman made clear in New Delhi is that these real shifts deserve honest acknowledgment — not corporate spin. For workers, policymakers, and business leaders alike, the challenge ahead is learning to separate genuine disruption from convenient narrative.
