Oracle has laid off between 20,000 and 30,000 employees globally, representing roughly 18% of its workforce, primarily to fund AI and cloud infrastructure expansion. Through the layoffs the company has raised $45–50 billion in debt and equity financing in 2026 to fund these projects, with layoffs expected to free up $8–10 billion in cash flow.
There is a trend: In 2025, AI was cited as a factor in nearly 55,000 layoffs in the U.S., with the majority occurring in the tech sector, including companies like Amazon, Microsoft, Salesforce, and CrowdStrike.
Oracle began executing mass layoffs on March 31, 2026, sending early-morning termination emails to employees across the US, India, Canada, Mexico, and other regions without prior warning.
The layoffs are part of a broader organisational restructuring aimed at reallocating resources to support the company’s aggressive investment in AI data centres and cloud infrastructure. Employees reported receiving emails around 6 a.m. local time, informing them that the day of the email would be their last working day.
Oracle’s mass layoffs this past week indicate that even highly skilled, mid-career professionals are no longer safe from disruption as companies reallocate billions toward AI.
According to Sharon Gai (former Alibaba executive and author of How to Do More with Less: Future-Proofing Yourself in an AI-driven Economy), US workers should take note.
Gai observes how “The companies that are laying off people are not financially struggling. See article I just wrote here. It’s a company making a capital-intensive bet on AI infrastructure that its current balance sheet cannot comfortably sustain, and eliminating tens of thousands of employees to close the gap.”
Workers pay the price for inward AI investment
In other words, investment in AI is driving savings and workers are paying the price. Gai’s research uncovers: “The freed-up cash (an estimated $8 to $10 billion) goes straight into AI data centres. Amazon, Microsoft, and Meta have all followed similar patterns. The message is: profitability no longer protects your job when your employer decides to bet big on AI.“
Diving deeper into the trends, Gai finds: “AI drove these cuts on two fronts. First, it created the spending pressure.” Citing the recent case, Gai adds: “Oracle is pursuing a $156 billion capital spending push tied to its cloud infrastructure, and it needed to free up cash to fund data centres for clients like OpenAI and Meta.”
AI = job cuts
Gai’s follow up point is: “AI is replacing the work itself. Some cuts targeted job categories Oracle expects it will need less of due to AI. Oracle’s co-CEO stated that AI coding tools are enabling smaller engineering teams to deliver more complete solutions more quickly. AI both created the financial hole and provided the rationale for which roles to eliminate.”
Who is at risk?
In terms of who is most at risk, it is not just entry level jobs, Gai finds. “Engineers, architects, database administrators, ERP implementation specialists, and operations staff were all affected. Entire teams in Revenue and Health Sciences and SaaS Virtual Operations Services saw reductions of at least 30%.”
Engineers face several risks from AI, including job displacement, misinformation, and challenges in integrating AI systems into existing workflows.
The pattern, Gai continues, is: “Operations and services roles involving repeatable workflows, mid-level engineering positions being compressed by AI coding tools, and industry-specific implementation specialists whose customisation work AI can accelerate.”
Even where jobs are retained, AI and automation appear to intensify capitalist dynamics by embedding managerial control within algorithmic systems. In turn, this expands data-driven surveillance and leads to a restructuring of value extraction. Hence, these AI technologies reduce worker autonomy, obscure decision-making mechanisms, and deepen power asymmetries between capital and labour
Greatest risk – the drive of automation and analytics
AI is reshaping the workforce by automating tasks, leading to significant job displacement in certain sectors, particularly white-collar and tech roles, while creating new opportunities in AI-related fields.
Hence, there are some forms of work at the greatest risk from the forward march of AI. Gai points out: “AI isn’t just threatening clerical work. It’s compressing demand for skilled knowledge workers in the middle of the organizational stack.”
