Oracle Cuts 'Thousands' of Jobs as Data Centre Spend Rises

Oracle is reportedly laying off 'thousands' of employees as it increases spending on AI infrastructure, with data centre capacity at the centre of its plans.

The BBC's estimates place job losses at 10,000, with further reductions possible as the company adjusts its workforce to align with capital investment in compute and storage.

An email to staff, reported by Business Insider, states that the decision was made “after careful consideration of Oracle’s current business needs”.

As of May 2025, Oracle employed around 162,000 people, making the scale of the restructuring applicable across both technical and operational teams.

AI infrastructure reshapes data centre demand

Oracle is directing investment towards expanding its data centre footprint, with plans to spend about US$50bn in CapEx on AI infrastructure during its 2026 fiscal year.

Speaking during a 2025 Q3 earnings call, Chairman and Chief Technology Officer Larry Ellison said the company is “bringing on enormous amounts of capacity over the next 24 months”, as it builds out its AI infrastructure.

These investments reflect how demand has grown from traditional applications towards AI-driven services. Data centres now need to support accelerated computing, often using specialised chips such as GPUs.

Automation reduces workforce requirements

At the same time, Oracle uses AI tools internally, which reduces the number of engineers required to deliver software.

Co-CEO Mike Sicilia explained this dynamic in March, telling investors that “the use of AI coding tools inside Oracle is enabling smaller engineering teams to deliver more complete solutions to our customers more quickly".

“We are building brand-new SaaS products using AI and also embedding AI agents right into our existing applications suites,” he added.

Oracle’s own statement reinforces this trend: “AI models for generating computer code have become so efficient that we have been restructuring our product development teams into smaller, more agile and productive groups.

“This new AI Code Generation technology is enabling us to build more software in less time with fewer people. Oracle is now building more SaaS applications for more industries at a lower cost.”

This shift directly affects staffing levels, particularly in product development teams where automation replaces repetitive coding tasks. As a result, investment flows away from labour and towards infrastructure.

Restructuring costs and industry-wide impact

Oracle increased its restructuring budget by US$500m in March 2026, bringing the total to more than US$2bn for the fiscal year. The budget covers redundancy packages and associated exit costs, reflecting the scale of workforce changes.

Analysis from TD Cowan suggests the total number of job cuts could reach between 20,000 and 30,000 across the fiscal year. 

Other technology companies are following a similar path, linking job cuts to rising investment in AI and data centres. Reuters recently suggested that Meta considers reducing its workforce by up to 20% to offset infrastructure spending.

Mark Zuckerberg, CEO and Founder of Meta, stated at a White House dinner that the company plans to invest “at least US$600m” in US infrastructure, including funding for new data centres.

Meta also announced that it was launching Meta Compute, a division focused on building and managing AI infrastructure.

This move highlights how data centre operations become a central function within large technology firms, rather than a supporting role.

Atlassian also announced plans to cut 10% of its workforce.

CEO Mike Cannon Brookes addressed the change, stating: “It would be disingenuous to pretend AI doesn't change the mix of skills we need or the number of roles required in certain areas. It does.”

Across the AI and data centre sector, companies are redirecting capital towards data centre expansion and AI infrastructure while reducing headcount in areas where automation replaces manual work.

This restructuring places data centres at the core of digital strategy, as demand for compute capacity continues to grow alongside AI adoption.