Oracle AI's Big Gamble: From Layoff Crisis to 50 Billion Funding Turnaround, Survival or Comeback?

Recently, a series of developments involving tech giant Oracle have been capturing the attention of global capital markets—from bad news about layoffs and self-rescue to dramatic reversals in massive financing. This veteran tech company is currently engaged in a life-and-death battle over the future in the AI infrastructure race.

On one side is the enormous capital pressure caused by expanding AI data centers; on the other is industry opportunities prompting attempts at breakthroughs. Every move Oracle makes has become a crucial entry point for interpreting the industry’s shifting fortunes.

Crisis Erupts

Layoffs and Financing Dilemmas Push the Company to the Brink

Oracle’s difficulties began with the out-of-control “money-burning game” of AI infrastructure. In an effort to keep pace with the global AI computing power surge, Oracle has heavily ramped up data center construction. However, the capital expenditure required far exceeded market expectations. According to a report by TD Cowen, to meet the demands of major clients like OpenAI, Meta, and Nvidia, Oracle’s total capital spending on AI infrastructure has reached $156 billion. Such a massive investment has plunged the company into serious financial distress.

The first domino effect of this financial pressure was the breakdown of financing channels. Several US banks recognized the risks of Oracle’s overexpansion and stopped providing loans for its data center projects. Market confidence in Oracle plummeted, with its stock price dropping from a high of $340 in September 2025 to around $140 in early February 2026—nearly a 60% decline, wiping out over $300 billion in market value. To make matters worse, by November 2025, Oracle’s net debt had reached $88.3 billion, with long-term lease liabilities approaching $250 billion. Free cash flow turned negative in Q2 of fiscal 2026, at -$13.2 billion—the worst since 1992. Moody’s and S&P also downgraded its outlook to negative, pushing it toward “junk” status.

To ease cash flow pressures, Oracle resorted to a drastic measure—laying off 20,000 to 30,000 employees, about 15% of its global workforce—its largest workforce reduction ever. The layoffs affected its global operations, including R&D centers in Shanghai, Shenzhen, Nanjing, and Suzhou, with nearly 500 employees leaving in the first wave.

The layoffs mainly targeted non-core businesses. The $28.3 billion acquisition of Cerner’s healthcare software division in 2022 became a major casualty, with many middle management and global support roles not directly involved in AI or computing power being cut significantly. Although Oracle announced a severance plan with N+6 months’ pay, it capped monthly salaries at 25,000 yuan and offered only a two-week buffer period for resignation—after which compensation would be sharply reduced—exposing its tight financial situation. It is estimated that these layoffs could free up $8 billion to $10 billion in cash, serving as a short-term “stopgap.”

More concerning is that the financial crisis has begun to impact core operations. By the end of 2025, Oracle had delayed the completion of some data centers planned for OpenAI from 2027 to 2028, citing shortages of skilled labor and supply chain issues. These data centers are critical for Oracle’s strategy to partner with OpenAI and capture AI computing market share. Delays only deepen market worries. Industry estimates suggest Oracle needs to borrow $25 billion annually to support its AI data center expansion. With banks halting lending and cash flows deteriorating, the company faced a situation where it had “no money to invest.”

Plot Twist

$50 Billion Financing “Heavy Hit,” Credit Ratings Rarely Upgraded

Just as the market believed Oracle was heading toward deeper crisis, a major announcement turned the tide dramatically. In early 2026, Oracle revealed a financing plan totaling $45–50 billion—its largest single-year fundraising effort—described by Barclays as a “equity rocket launcher,” marking a crucial step to save the company.

This financing plan was highly targeted, balancing debt relief with asset-liability management.

Approximately $25 billion would come from equity issuance, including common stock, mandatory convertible preferred shares, and a “market-based equity issuance plan” of up to $20 billion. The remaining $20–25 billion would be raised through issuing unsecured preferred bonds with maturities ranging from 3 to 40 years, effectively diversifying refinancing risk and aligning with the long-term investment cycle of AI data centers.

Oracle’s management explicitly stated that all proceeds would be used to expand cloud infrastructure (OCI), focusing on AI data center construction to fulfill computing power supply contracts with major clients. They also pledged “one-time bond issuance with no additional debt in the same year,” signaling market stability.

The announcement quickly restored market confidence. Barclays was among the first to upgrade Oracle’s credit rating from “speculative” to “investment grade,” with a target price of $310. Analysts noted that Oracle’s current 18x forward P/E ratio for 2027 was disconnected from its projected growth of over 30% in the coming years, leaving about 80% upside potential.

Barclays analysts pointed out that this financing effectively eliminated the biggest concern about Oracle’s AI expansion funding. The combination of equity and mandatory convertible securities could reduce peak leverage by 0.4 times. Although this would dilute existing shareholders by up to 4%, it would significantly strengthen the balance sheet and refocus investor attention on the company’s growth potential in AI.

In essence, Oracle’s core logic for this financing was to dilute equity in exchange for long-term development space. Management chose to sacrifice some shareholder interests to avoid over-leverage and credit rating downgrades. This “short-term sacrifice for long-term stability” has temporarily aligned the interests of creditors and shareholders and demonstrated Oracle’s commitment to its AI infrastructure race. So far, the plan has gained initial approval from the capital markets, with the stock gradually rebounding from lows and shedding its previous downward trend.

Breakthrough Attempts

Innovative Models Hedge Risks, Hidden Dangers Remain

Beyond massive financing, Oracle is exploring innovative business models to fundamentally control capital expenditure and ease financial pressures.

One key approach is the “Bring Your Own Chip (BYOC)” model. Since GPUs account for over half the cost of data center construction, and Nvidia’s GB200 modules sell for tens of thousands of dollars each, Oracle has already deployed over 96,000 Nvidia GB200 chips in its data centers. The high cost of chip procurement exerts enormous financial pressure.

The BYOC model allows customers to purchase expensive GPU chips themselves, while Oracle provides only the infrastructure, operations, and network support. This significantly reduces Oracle’s capital investment. Leveraging its OCI platform’s technical advantages—such as RDMA InfiniBand networking, which reduces internal data center latency to 2 microseconds (10 times faster than Ethernet)—Oracle can support large-scale AI clusters with thousands of GPUs, continuing to lock in customers.

Meanwhile, Oracle is also trying to hedge risks by optimizing its business structure and improving operational efficiency. It is integrating Cerner’s healthcare software division, launching the Autonomous Shield plan to accelerate migration of medical EHR systems to OCI, and exploring vertical markets in healthcare cloud. Additionally, by leveraging its “database + cloud infrastructure + enterprise applications + industry solutions” full-stack advantage, Oracle promotes cross-selling and increases customer ARPU, using high-margin cloud services to offset the low margins of AI infrastructure.

According to Oracle’s Q2 FY2026 financial report, its cloud revenue reached $8 billion, accounting for 50% of total revenue. OCI cloud infrastructure revenue was $3.3 billion, up 55% year-over-year, with GPU-related revenue soaring 177%. These have become core growth engines. The company’s remaining performance obligations (RPO) stood at $523 billion, providing some support for future growth.

However, these breakthrough strategies still do not fully resolve Oracle’s fundamental risks. First, the capital expenditure gap remains huge—out of the $156 billion total demand, the $50 billion financing only covers about one-third. Continued large investments are needed over the next 3–5 years, and the $25 billion annual borrowing requirement will keep debt service under heavy pressure. Second, customer concentration risk is high: over 70% of OCI’s new orders come from OpenAI, which itself is projected to incur a cumulative loss of $115 billion by 2029. Its ability to fulfill contracts is uncertain; if its financing is blocked or it reduces computing power procurement, Oracle could face serious capacity idle risks. Third, industry competition is intensifying, with AWS, Azure, and Google Cloud accelerating their AI infrastructure investments, leading to price wars and technological pressures that could erode Oracle’s market share. The long construction cycles of data centers and rapid GPU tech iteration may also cause “built-to-become-outdated” scenarios.

Additionally, the long-term effects of equity dilution cannot be ignored. The $25 billion equity raise will dilute existing shareholders’ stakes, suppress EPS, and if AI growth underperforms, shareholders may vote with their feet, further increasing financing pressure. Oracle’s previous bond issuance in September 2025, without disclosing future financing needs, led to a class-action lawsuit from bond investors and damaged its credit trust. While the current financing plan temporarily stabilizes the situation, long-term credit recovery will take time.

Ultimate Game

$50 Billion Is Just Life Support; Turning the Tide Depends on Three Key Factors

Overall, Oracle’s $50 billion financing is essentially a “time buy for space”—a survival move rather than a definitive turnaround. In the short term, it alleviates liquidity fears, covering core capital needs for 1–2 years, preventing a liquidity crisis. The credit rating upgrade and stock rebound also reflect market confidence. Layoffs and innovation efforts can further ease short-term cash pressures, giving the company breathing room.

But in the long run, whether Oracle can truly turn around depends on three critical variables. The ultimate outcome of this AI gamble remains uncertain.

First, the speed of order fulfillment and revenue realization

Oracle’s $523 billion in unfulfilled orders could translate into sustained high growth if over 90% of these orders are delivered on time, converting into revenue from cloud and OCI. This would gradually restore cash flow, cover capital expenditures, and reduce debt, creating a positive cycle. Conversely, if major clients delay or cut spending, or if data center construction continues to be postponed, the $50 billion financing will be exhausted, and the company could face even more severe debt crises.

Second, control of capital expenditure and effectiveness of new business models

Whether the “Bring Your Own Chip” model gains widespread acceptance and truly reduces capital costs is crucial for Oracle to escape the “burn money for scale” trap. Similarly, the efficiency gains from layoffs and the integration of non-core businesses must continue to generate cash flow without hindering AI development.

Third, the ability to respond to industry competition and technological evolution

In the AI infrastructure arms race, Oracle’s ability to maintain technological advantages against AWS, Azure, and Google Cloud, and to avoid falling into price wars that erode margins, is vital. Balancing data center construction cycles with rapid GPU tech updates to prevent capacity idle and obsolescence will directly influence its position in the AI computing market.

From an industry perspective, Oracle’s challenges and strategies reflect the broader global AI infrastructure sector. The explosive growth in AI computing demand has driven enormous capital investments, but the heavy assets, long cycles, and high risks also pose unprecedented challenges for participants.

Oracle’s choice to gamble on massive financing and equity dilution to pursue future growth is both a necessity and a proactive industry move—if successful, it could transform from a traditional software vendor into a leading AI cloud service provider, dominating the AI computing race. If it fails, it risks an irreversible debt crisis and may be forced to shrink its AI infrastructure ambitions.

Currently, Oracle’s $50 billion financing has extended its survival, but the path to a true turnaround remains uncertain.

Short-term survival is only the first step. Converting funds into capacity, orders into revenue, and innovation into core competitiveness are the real challenges ahead. The game for the future continues, and every move Oracle makes will offer valuable lessons and insights for the development of the global AI infrastructure industry.