REDWOOD CITY, California — Oracle is reportedly planning thousands of layoffs as it faces mounting costs tied to expanding artificial intelligence infrastructure and large-scale data centers, according to a Bloomberg report, March 6. The job cuts are expected to begin within the coming weeks as the company restructures operations to support its growing AI investment.
Bloomberg reported that the layoffs could affect “thousands” of employees, though the exact number remains unclear because planning is still underway. The reductions are expected to affect multiple divisions across the company.
Some of the targeted roles may be positions viewed as less necessary because of increasing automation and AI-driven processes, according to the report. Oracle has also reviewed open job listings in its cloud division, potentially freezing or slowing hiring for some positions as part of a broader cost-control effort.
The reported cuts follow earlier reductions. In 2025, Oracle eliminated about 3,000 jobs, including significant layoffs in India. In January 2026, the company also laid off more than 250 employees in the San Francisco Bay Area.
A research report from TD Cowen previously predicted Oracle could cut between 20,000 and 30,000 jobs to improve financial flexibility and free up an estimated $8 billion to $10 billion in cash flow.
Oracle has already disclosed a restructuring plan that could cost up to $1.6 billion, including severance for affected employees, through its fiscal year ending in May.
The company’s cost-cutting comes as it aggressively invests in AI infrastructure and large-scale data centers to compete with cloud rivals Amazon and Microsoft. Analysts have warned that those investments could pressure Oracle’s cash flow for years, with returns potentially not materializing until about 2030.
“Both equity and EBT investors have raised questions regarding Oracle’s ability to finance this buildout,” TD Cowen said in its research report.
The reported layoffs underscore a broader shift across the tech industry, where companies are cutting costs and restructuring operations to finance increasingly expensive AI ambitions.