Oracle has cut over 300 jobs across its U.S. operations, with 143 positions eliminated in Redwood City, California, and 161 in Seattle, Washington, according to Worker Adjustment and Retraining Notification (WARN) filings. The layoffs represent part of Oracle’s strategic shift toward AI infrastructure investments, though the company has been more restrained in workforce reductions compared to other tech giants that have eliminated tens of thousands of positions.
What you should know: The actual scope of Oracle’s layoffs may be significantly larger than officially reported figures suggest.
• An Oracle worker familiar with the situation told The Register that the numbers “sound low,” estimating “low thousands worldwide” could be affected.
• Remote workers might not be accounted for in WARN filings, a tactic Microsoft has also been accused of using to obscure layoff scale.
• The source indicated “this is just the start,” with potential office closures and cuts affecting around 10% of Oracle’s Indian workforce.
The big picture: Oracle’s workforce reductions remain modest compared to massive layoffs at other tech companies, reflecting a more conservative approach to economic uncertainties.
• Around 200 Oracle workers left in 2022, with additional departures in separate rounds since then.
• This contrasts sharply with tens of thousands of job cuts at Amazon, Google, and Microsoft, making Oracle employees “pretty safe” by comparison.
Why this matters: Companies are redirecting capital from staffing budgets to AI data center expansions rather than AI directly replacing human workers.
• Oracle confirmed an 8% revenue increase for fiscal 2025 in June, with CEO Safra Catz noting that “Cloud Infrastructure growth rate is expected to increase from 50% in FY25 to over 70% in FY26.”
• The layoffs highlight how AI’s impact on employment is more complex than simple job displacement, involving strategic resource reallocation toward infrastructure investments.
Looking ahead: Oracle’s financial performance suggests the company is positioning itself for accelerated cloud infrastructure growth while managing workforce costs to fund AI-related capital expenditures.
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