To fulfill its AI ambitions, Oracle has convinced itself using the 'letting go' philosophy. A Wall Street analyst noted that, in the long term, layoffs will free up cash flow and increase the company’s overall revenue.
Database software and cloud computing giants $Oracle (ORCL.US)$ are employing workforce reductions to aggressively cut costs in support of their ambitious artificial intelligence initiatives. This round of layoffs occurs against the backdrop of a broader trend where major technology companies, including $Oracle (ORCL.US)$ 、 $Microsoft (MSFT.US)$ and $Alphabet-C (GOOG.US)$ , are significantly increasing investments in AI infrastructure. This multinational technology conglomerate is seeking to eliminate thousands of positions in order to free up substantial capital for the development of artificial intelligence data center infrastructure.
According to media reports citing sources familiar with the matter, this tech giant has informed its workforce of 162,000 employees that the new round of layoffs will affect tens of thousands of workers.
Oracle declined to comment on the latest layoff news. Some Wall Street analysts stated that, from a long-term perspective, the layoffs will release cash flow and reallocate more resources from low-return segments to high-growth areas, significantly boosting the company’s overall revenue.
Investors remain uneasy about the company's massive AI capital expenditures on hyperscale AI data centers designed to handle astronomical AI workloads. Although Oracle’s stock price rebounded by 5% this week due to signs of easing geopolitical tensions in the Middle East, its stock has fallen more than 25% year-to-date.
In early February, the company announced plans to raise up to $50 billion through a combination of debt and equity financing by the calendar year 2026. The funds will be used to aggressively expand its already massive cloud infrastructure capacity, which is closely tied to the contracted demand for AI training and inference computing resources in the cloud. Core clients include $NVIDIA (NVDA.US)$ , the parent company of Facebook, $Meta Platforms (META.US)$ , OpenAI, $Advanced Micro Devices (AMD.US)$ and xAI.
As model sizes, reasoning chains, and multimodal/agent-based Agentic AI workloads drive exponential growth in computing resource consumption, tech giants are increasingly focusing their capital expenditure on AI computing infrastructure under surging AI demand. Global investors continue to anchor the “AI computing power bull market narrative” around NVIDIA’s AI GPUs, Google’s TPU clusters, AMD’s product iterations, and AI computing cluster delivery expectations as one of the most certain prosperity investment narratives in global equities.
American tech giants like Oracle are at the intersection of two unsettling trends roiling the technology sector.
According to the latest analyst expectations compiled by institutions, $Amazon (AMZN.US)$ together with $Alphabet-A (GOOGL.US)$ , the parent company of Facebook, $Meta Platforms (META.US)$ , and $Oracle (ORCL.US)$ and $Microsoft (MSFT.US)$ are projected to reach a cumulative AI-related capital expenditure of approximately $650 billion by 2026. Some analysts believe that total spending could exceed $700 billion – implying a year-on-year increase in AI capital expenditure of more than 70%.
Notably, these five major U.S. super tech giants are projected to cumulatively invest around USD 1.5 trillion between 2023 and 2026 to build an incredibly vast AI computing power infrastructure. By comparison, these tech giants invested approximately USD 600 billion cumulatively during the entire historical period prior to 2022.
However, these immense AI expenditures will substantially reduce the companies’ free cash flow while short-term returns lack clear AI-related monetization and revenue generation pathways, increasing investor concerns. Investors are worried about when the growing investments in AI computing infrastructure will yield more significant returns in revenue and profit growth. Additionally, the pessimistic narrative of “AI disrupting everything” has led global investors to continuously sell off software stocks, including those of the five major tech giants, causing their stock prices to remain sluggish this year. Notably, Microsoft’s stock fell 23% in the first quarter, marking its worst quarterly performance since the 2008 financial crisis.
Wall Street strongly supports Oracle’s layoffs, emphasizing they will help save costs.
Analysts at Barclays, the Wall Street financial giant, stated in a research report on Tuesday that Oracle’s layoffs would help release strong cash flow in the short to medium term. The institution reiterated its “Overweight” rating for the stock and set a 12-month target price of $230. As of Wednesday’s U.S. market close, Oracle’s share price closed at $145.230.
“Given Oracle’s existing large-scale restructuring plan for fiscal year 2026 and previous related media reports, we do not believe the currently announced layoffs will surprise the market. The market seems to recognize the cost-saving potential embedded in Oracle’s latest measures amid the rapid expansion of its core AI infrastructure capacity, as well as the robust revenue expectations driven by the AI infrastructure boom,” analysts from Barclays commented.
Barclays also emphasized that Oracle's profit output per employee is lower than that of its competitors, and its workforce productivity is below the average level. The latest forecast data from Barclays analysts shows that Oracle’s revenue will grow to at least three times the current level in the coming years due to limited employee growth compared to other cloud computing giants and significantly reduced operating costs.
Unlike Block’s 'brutal layoffs' driven by AI agent technology, Oracle is focusing on the arms race for AI computing power.
For Oracle, this round of large-scale layoffs appears to be more about freeing up cash flow for the AI computing infrastructure arms race, stabilizing investor sentiment, and improving capital efficiency, rather than the company having definitively proven that 'AI-driven workflows are sufficient to directly replace a large number of employees.'
Public information shows that while Oracle has initiated layoffs affecting thousands of people, it is also advancing an intensive expansion of AI infrastructure. The company recently planned to raise up to $50 billion for capacity expansion, and its stock price has fallen significantly by approximately 29% year-to-date. However, at the same time, Oracle has demonstrated strong demand for AI computing resources: Remaining Performance Obligations (RPO) surged 325% year-over-year to $553 billion, and the company raised its revenue target for the fiscal year 2027 to $90 billion. In other words, the narrative of 'AI disrupting everything' has a real and substantial impact on Oracle’s fundamentals, but it seems more like reshaping capital expenditures, free cash flow, and valuation frameworks first, before gradually influencing organizational structure.
Block, led by Twitter co-founder Jack Dorsey, laid off over 4,000 employees in one move, nearly half of the tech company’s workforce. The company’s public statements indicate that AI agent-based proxy tools enable smaller teams to maintain higher operational efficiency. Its CFO later stated that the significant improvement in operational efficiency brought by AI agent-focused proxy workflows has made deep layoffs almost 'inevitable' for any enterprise.
In contrast, although Oracle has recently restructured its Fusion cloud software to focus on agent-based AI workflows (Agent AI/Agentic AI), aiming to automate business outcomes and numerous repetitive processes, the company’s publicly stated rationale for layoffs remains primarily about restructuring, cost reduction, and reallocating resources to build AI data centers, rather than adopting $Block (XYZ.US)$ 's narrative of 'AI being sufficient to replace traditional organizational hierarchies' as the main reason for layoffs. For Oracle, a stronger rationale for layoffs lies in the explosive growth in AI computing power demand, which is driving GPU infrastructure, power equipment, and financing needs for data centers to extremely high levels. The company must reallocate resources from low-return areas to high-growth segments.
Editor/Doris