Oracle’s $18 Billion AI Data-Center Debt: Is the AI Buildout Becoming Too Leveraged?

Educational research only — not investment advice.

Oracle stock is becoming a major test of whether the AI infrastructure boom is taking on too much debt.

Around $18 billion of loans linked to Oracle’s planned Project Jupiter data center in New Mexico are now trading below their original value.

The problem is simple:

AI demand is booming—but building the infrastructure requires enormous amounts of capital.

What Is Project Jupiter?

Project Jupiter is a huge AI data-center development planned in New Mexico.

The project is connected to Oracle’s expanding cloud partnership with OpenAI and forms part of the infrastructure needed to run increasingly powerful AI models.

Banks including Santander and Jefferies helped arrange roughly $18 billion of financing.

But those loans are now being quoted at around 89 to 91 cents on the dollar, showing investors want a discount before taking the risk.

Why Is the Debt Under Pressure?

There are several concerns.

Oracle is already borrowing heavily to finance its AI expansion.

Reuters reported that Oracle had around $129.5 billion of debt and roughly $260 billion of long-term data-center lease commitments earlier this year.

At the same time, free cash flow has weakened because infrastructure spending is rising rapidly.

That creates a difficult equation:

more AI investment → more future revenue potential → more debt today

Investors now want proof that the future revenue will justify the financing.

Oracle Is Close to Junk Status

Credit-rating agencies are becoming more cautious.

S&P downgraded Oracle to BBB-, only one level above speculative-grade or “junk” status.

That matters because a further downgrade could make borrowing more expensive.

Higher interest costs would make the economics of future data-center projects less attractive.

For a company spending tens of billions on infrastructure, even a small increase in financing costs can become significant.

The New Mexico Project Has Other Problems

Debt is not the only issue.

Project Jupiter also faces local opposition over:

  • water consumption
  • air pollution
  • power generation
  • environmental permits

Plans for a natural-gas pipeline serving the facility’s proposed 2.2 gigawatts of gas-powered generation have faced regulatory difficulties.

Delays matter because debt continues to cost money even when a project is not producing revenue.

That increases execution risk.

Why OpenAI Matters

Oracle’s AI expansion is closely tied to expected demand from OpenAI.

That creates enormous potential—but also concentration risk.

Reuters has reported that about half of Oracle’s huge future revenue backlog is linked to OpenAI-related business.

OpenAI itself is spending heavily.

The company reportedly expects cumulative cash burn of around $278 billion between 2026 and 2030 as it expands computing capacity.

That means the AI infrastructure ecosystem increasingly depends on several companies continuing to raise enormous amounts of capital.

Is the AI Boom Becoming Too Leveraged?

Not necessarily—but the financing structure is changing.

Earlier AI growth was largely funded by cash-rich technology giants.

Increasingly, the industry is using:

corporate debt + project loans + leases + private credit

to fund data centers, power infrastructure and chips.

Global AI infrastructure spending is expected to approach $795 billion in 2026 and could exceed $1 trillion next year.

As those numbers grow, lenders will become more selective.

What Should Investors Watch?

Watch Oracle debt, free cash flow, credit ratings, AI capital spending and Project Jupiter delays.

The key question is:

Can Oracle’s AI revenue grow fast enough to justify the debt needed to build the infrastructure?

If revenue and cash flow catch up, the leverage may look manageable.

If projects are delayed or AI spending slows, debt could become a much bigger problem for Oracle stock.

Track AI Infrastructure Risk With TradingSimuLab

TradingSimuLab’s Macro and Risk tools help users study changing technology spending, financial conditions and market risk.

For more quantitative market research and educational trading tools, sign up to TradingSimuLab.

TradingSimuLab is for educational and research purposes only and does not provide investment advice.

Continue exploring TradingSimuLab.

  • How to Read the Four Macro Scenarios

    TradingSimuLab’s Macro Model reduces a complicated economic backdrop into four scenario states: These scenarios summarize the model’s view of conditions such as monetary policy, inflation, the yield curve, credit spreads, consumer sentiment, and broader liquidity. They are not direct recession, stagflation, or soft-landing forecasts. Instead, they provide a structured way to answer: How supportive or…

  • Alphabet (GOOGL) Stock Outlook: Constructive, but Not Fully Confirmed

    Model snapshot: May 30, 2026 Alphabet (GOOGL) showed a constructive but not fully confirmed setup in TradingSimuLab’s five-model framework on May 30, 2026. The positive signals came from Trend Persistence, relatively low fakeout pressure, and a supportive Macro Model. The main weaknesses were modest Trend Strength and a defensive Risk Simulation showing meaningful potential drawdown.…

  • Five-Model Trading Framework Explained

    Trading markets with one indicator creates a simple problem: one indicator can answer only one type of question. A trend can be strong but overextended. A breakout can trigger but still carry high fakeout risk. The technical picture can look constructive while the macro backdrop deteriorates. And even an attractive setup can have uncomfortable simulated…

  • Fakeout Risk in the Timing Model: How to Read Breakout Failure Risk

    A breakout can trigger without becoming a successful breakout. Price may move through an important market level, appear to establish a new direction, and then quickly lose momentum. If the move cannot hold and price returns toward its previous range, the apparent breakout may become a fakeout, also known as a false or failed breakout.…

  • Fakeout Risk Explained

    A breakout can look convincing at first and still fail. Price moves through an important level. Momentum appears to strengthen. The market seems ready to establish a new directional move. Then the breakout loses momentum. Price falls back into the previous range, the apparent confirmation disappears, and what initially looked like a new trend becomes…

  • Expected Return vs Risk-Reward: Reading Simulation Quality More Carefully

    A positive expected return can look attractive. But by itself, it tells you surprisingly little about the quality of a simulated investment outcome. Imagine two assets. Both have an expected simulated return of +10%. At first glance, they appear equally attractive. But suppose the first simulation shows relatively contained downside paths, a high probability of…

  • Exhaustion Risk in Trend Detector: When Strong Trends Become Fragile

    A strong trend can be one of the easiest market structures to recognize — and one of the easiest to misread. When price has been moving persistently in one direction, trend strength can look impressive. The chart may appear organized, the directional move may still be intact, and recent performance may reinforce the impression that…

  • Exhaustion Risk Explained

    A strong trend is not necessarily a comfortable trend. An asset can continue moving decisively higher or lower while the structure behind that move becomes increasingly stretched, mature, crowded, or vulnerable to a period of cooling. That is the purpose of Exhaustion Risk inside TradingSimuLab’s Trend Detector. Exhaustion Risk is a caution layer. It helps…

  • EMA Slope and Distance From Trend Explained in Trend Detector

    A market can move higher without having a particularly healthy trend underneath it. It can also pull back temporarily while the broader trend structure remains intact. That distinction is why TradingSimuLab’s Trend Detector does not look only at whether price is moving up or down. It also considers the behavior of the trend base itself…