As AI Surges, Layoffs Hit Worst Moment Since 2009 During Throes of Financial Crisis
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As AI Surges, Layoffs Hit Worst Moment Since 2009 During Throes of Financial Crisis
"US employers announced over 108,000 layoffs across January, in the highest to start the year since the depths of the Great Recession in 2009. Many executives were quick to blame AI for the layoffs, though the real reason might be simpler: companies just aren't optimistic about the direction the economy is heading. According to new reporting by CNBC, layoffs are up 118 percent from January, 2025, and a whopping 205 percent compared to December 2025. Throughout the month, US corporations tracked by analyst firm Challenger, Gray and Christmas only reported 5,306 new hires - another low which hadn't been seen since January of 2009."
"With so much hope for AI's future, it's no wonder many commentators and businesses titans have blamed the tech for the bone-dry job market. Yet as the market research firm Forrester explained in its January labor report, the "job apocalypse" is way overblown. "Many companies announcing AI-related layoffs do not have mature, vetted AI applications ready to fill those roles, highlighting a trend of 'AI washing' - attributing financially motivated cuts to future AI implementation," the report read. In fact, some companies' financial woes might actually be the result of AI-washing in previous years. As Forrester puts it, "over-automating roles due to the hype surrounding AI can lead to costly pullbacks,""
Over 108,000 US layoffs occurred in January 2026, marking the largest January total since 2009. Layoffs rose 118 percent year-over-year and 205 percent month-over-month. Employers reported only 5,306 new hires during the month, the lowest hiring level since January 2009. Many layoff plans were set at the end of 2025, signaling reduced employer optimism about 2026 economic prospects. Tech firms plan major increases in AI capital expenditures, with Alphabet intending to nearly double AI spending. Market research firm Forrester warns that many AI-related cuts reflect "AI washing" and that premature over-automation can force costly reversals.
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