Introduction
Artificial intelligence may be the most powerful technology of the century—but behind the demos, the breakthroughs, and the trillion-dollar valuations, a very different story is unfolding in the credit markets. CDS traders, structured finance desks, and risk analysts have quietly begun hedging against a scenario the broader industry refuses to contemplate: that the AI boom may be running ahead of its cash flows, its customers, and its capacity to sustain the massive debt fueling its datacenter expansion. The Oracle–OpenAI megadeals, trillion-dollar infrastructure plans, and unprecedented borrowing across the sector may represent the future—or the early architecture of a credit bubble that will only be obvious in hindsight. As equity markets celebrate the AI revolution, the people paid to price risk are asking a far more sobering question: What if the AI boom is not underpriced opportunity, but overleveraged optimism?
Over the last few months, we’ve seen a sharp rise in credit default swap (CDS) activity tied to large tech names funding massive AI data center expansions. Trading volume in CDS linked to some hyperscalers has surged, and the cost of protection on Oracle’s debt has more than doubled since early fall, as banks and asset managers hedge their exposure to AI-linked credit risk. Bloomberg
At the same time, deals like Oracle’s reported $300B+ cloud contract with OpenAI and OpenAI’s broader trillion-dollar infrastructure commitments have become emblematic of the question hanging over the entire sector:
Are we watching the early signs of an AI credit bubble, or just the normal stress of funding a once-in-a-generation infrastructure build-out?
This post takes a hard, finance-literate look at that question—through the lens of datacenter debt, CDS pricing, and the gap between AI revenue stories and today’s cash flows.
1. Credit Default Swaps: The Market’s Geiger Counter for Risk
A quick refresher: CDS are insurance contracts on debt. The buyer pays a premium; the seller pays out if the underlying borrower defaults or restructures. In 2008, CDS became infamous as synthetic ways to bet on mortgage credit collapsing.
In a normal environment:
- Tight CDS spreads ≈ markets view default risk as low
- Widening CDS spreads ≈ rising concern about leverage, cash flow, or concentration risk
The recent spike in CDS pricing and volume around certain AI-exposed firms—especially Oracle—is telling:
- The cost of CDS protection on Oracle has more than doubled since September.
- Trading volume in Oracle CDS reached roughly $4.2B over a six-week period, driven largely by banks hedging their loan and bond exposure. Bloomberg
This doesn’t mean markets are predicting imminent default. It does mean AI-related leverage has become large enough that sophisticated players are no longer comfortable being naked long.
In other words: the credit market is now pricing an AI downside scenario as non-trivial.
2. The Oracle–OpenAI Megadeal: Transformational or Overextended?
The flashpoint is Oracle’s partnership with OpenAI.
Public reporting suggests a multi-hundred-billion-dollar cloud infrastructure deal, often cited around $300B over several years, positioning Oracle Cloud Infrastructure (OCI) as a key pillar of OpenAI’s long-term compute strategy. CIO+1
In parallel, OpenAI, Oracle and partners like SoftBank and MGX have rolled the “Stargate” concept into a massive U.S. data-center platform:
- OpenAI, Oracle, and SoftBank have collectively announced five new U.S. data center sites within the Stargate program.
- Together with Abilene and other projects, Stargate is targeting ~7 GW of capacity and over $400B in investment over three years. OpenAI
- Separate analyses estimate OpenAI has committed to $1.15T in hardware and cloud infrastructure spend from 2025–2035 across Oracle, Microsoft, Broadcom, Nvidia, AMD, AWS, and CoreWeave. Tomasz Tunguz
These numbers are staggering even by hyperscaler standards.
From Oracle’s perspective, the deal is a once-in-a-lifetime chance to leapfrog from “ERP/database incumbent” into the top tier of cloud and AI infrastructure providers. CIO+1
From a credit perspective, it’s something else: a highly concentrated, multi-hundred-billion-dollar bet on a small number of counterparties and a still-forming market.
Moody’s has already flagged Oracle’s AI contracts—especially with OpenAI—as a material source of counterparty risk and leverage pressure, warning that Oracle’s debt could grow faster than EBITDA, potentially pushing leverage to ~4x and keeping free cash flow negative for an extended period. Reuters
That’s exactly the kind of language that makes CDS desks sharpen their pencils.
3. How the AI Datacenter Boom Is Being Funded: Debt, Everywhere
This isn’t just about Oracle. Across the ecosystem, AI infrastructure is increasingly funded with debt:
- Data center debt issuance has reportedly more than doubled, with roughly $25B in AI-related data center bonds in a recent period and projections of $2.9T in cumulative AI-related data center capex between 2025–2028, about half of it reliant on external financing. The Economic Times
- Oracle is estimated by some analysts to need ~$100B in new borrowing over four years to support AI-driven datacenter build-outs. Channel Futures
- Oracle has also tapped banks for a mix of $38B in loans and $18B in bond issuance in recent financing waves. Yahoo Finance+1
- Meta reportedly issued around $30B in financing for a single Louisiana AI data center campus. Yahoo Finance
Simultaneously, OpenAI’s infrastructure ambitions are escalating:
- The Stargate program alone is described as a $500B+ project consuming up to 10 GW of power, more than the current energy usage of New York City. Business Insider
- OpenAI has been reported as needing around $400B in financing in the near term to keep these plans on track and has already signed contracts that sum to roughly $1T in 2025 alone, including with Oracle. Ed Zitron’s Where’s Your Ed At+1
Layer on top of that the broader AI capex curve: annual AI data center spending forecast to rise from $315B in 2024 to nearly $1.1T by 2028. The Economic Times
This is not an incremental technology refresh. It’s a credit-driven, multi-trillion-dollar restructuring of global compute and power infrastructure.
The core concern: are the corresponding revenue streams being projected with commensurate realism?
4. CDS as a Real-Time Referendum on AI Revenue Assumptions
CDS traders don’t care about AI narrative—they care about cash-flow coverage and downside scenarios.
Recent signals:
- The cost of CDS on Oracle’s bonds has surged, effectively doubling since September, as banks and money managers buy protection. Bloomberg
- Trading volumes in Oracle CDS have climbed into multi-billion-dollar territory over short windows, unusual for a company historically viewed as a relatively stable, investment-grade software vendor. Bloomberg
What are they worried about?
- Concentration Risk
Oracle’s AI cloud future is heavily tied to a small number of mega contracts—notably OpenAI. If even one of those counterparties slows consumption, renegotiates, or fails to ramp as expected, the revenue side of Oracle’s AI capex story can wobble quickly. - Timing Mismatch
Debt service is fixed; AI demand is not.
Datacenters must be financed and built years before they are fully utilized. A delay in AI monetization—either at OpenAI or among Oracle’s broader enterprise AI customer base—still leaves Oracle servicing large, inflexible liabilities. - Macro Sensitivity
If economic growth slows, enterprises might pull back on AI experimentation and cloud migration, potentially flattening the growth curve Oracle and others are currently underwriting.
CDS spreads are telling us: credit markets see non-zero probability that AI revenue ramps will fall short of the most optimistic scenarios.
5. Are AI Revenue Projections Outrunning Reality?
The bull case says:
These are long-dated, capacity-style deals. AI demand will eventually fill every rack; cloud AI revenue will justify today’s capex.
The skeptic’s view surfaces several friction points:
- OpenAI’s Monetization vs. Burn Rate
- OpenAI reportedly spent $6.7B on R&D in the first half of 2025, with the majority historically going to experimental training runs rather than production models. Ed Zitron’s Where’s Your Ed At Parallel commentary suggests OpenAI needs hundreds of billions in additional funding in short order to sustain its infrastructure strategy. Ed Zitron’s Where’s Your Ed At
- Enterprise AI Adoption Is Still Shallow
Most enterprises remain stuck in pilot purgatory: small proof-of-concepts, modest copilots, limited workflow redesign. The gap between “we’re experimenting with AI” and “AI drives 20–30% of our margin expansion” is still wide. - Model Efficiency Is Improving Fast
If smaller, more efficient models close the performance gap with frontier models, demand for maximal compute may underperform expectations. That would pressure utilization assumptions baked into multi-gigawatt campuses and decade-long hardware contracts. - Regulation & Trust
Safety, privacy, and sector-specific regulation (especially in finance, healthcare, public sector) may slow high-margin, high-scale AI deployments, further delaying returns.
Taken together, this looks familiar: optimistic top-line projections backed by debt-financed capacity, with adoption and unit economics still in flux.
That’s exactly the kind of mismatch that fuels bubble narratives.
6. Theory: Is This a Classic Minsky Moment in the Making?
Hyman Minsky’s Financial Instability Hypothesis outlines a familiar pattern:
- Displacement – A new technology or regime shift (the Internet; now AI).
- Boom – Rising investment, easy credit, and growing optimism.
- Euphoria – Leverage increases; investors extrapolate high growth far into the future.
- Profit Taking – Smart money starts hedging or exiting.
- Panic – A shock (macro, regulatory, technological) reveals fragility; credit tightens rapidly.
Where are we in that cycle?
- Displacement and Boom are clearly behind us.
- The euphoria phase looks concentrated in:
- trillion-dollar AI infrastructure narratives
- multi-hundred-billion datacenter plans
- funding forecasts that assume near-frictionless adoption
- The profit-taking phase may be starting—not via equity selling, but via:
- CDS buying
- spread widening
- stricter credit underwriting for AI-exposed borrowers
From a Minsky lens, the CDS market’s behavior looks exactly like sophisticated participants quietly de-risking while the public narrative stays bullish.
That doesn’t guarantee panic. But it does raise a question:
If AI infrastructure build-outs stumble, where does the stress show up first—equity, debt, or both?
7. Counterpoint: This Might Be Railroads, Not Subprime
There is a credible argument that today’s AI debt binge, while risky, is fundamentally different from 2008-style toxic leverage:
- These projects fund real, productive assets—datacenters, power infrastructure, chips—rather than synthetic mortgage instruments.
- Even if AI demand underperforms, much of this capacity can be repurposed for:
- traditional cloud workloads
- high-performance computing
- scientific simulation
- media and gaming workloads
Historically, large infrastructure bubbles (e.g., railroads, telecom fiber) left behind valuable physical networks, even after investors in specific securities were wiped out.
Similarly, AI infrastructure may outlast the most aggressive revenue assumptions:
- Oracle’s OCI investments improve its position in non-AI cloud as well. The Motley Fool+1
- Power grid upgrades and new energy contracts have value far beyond AI alone. Bloomberg+1
In this framing, the “AI bubble” might hurt capital providers, but still accelerate broader digital and energy infrastructure for decades.
8. So Is the AI Bubble Real—or Rooted in Uncertainty?
A mature, evidence-based view has to hold two ideas at once:
- Yes, there are clear bubble dynamics in parts of the AI stack.
- Datacenter capex and debt are growing at extraordinary rates. The Economic Times+1
- Oracle’s CDS and Moody’s commentary show real concern around concentration risk and leverage. Bloomberg+1
- OpenAI’s hardware commitments and funding needs are unprecedented for a private company with a still-evolving business model. Tomasz Tunguz+1
- No, this is not a pure replay of 2008 or 2000.
- Infrastructure assets are real and broadly useful.
- AI is already delivering tangible value in many production settings, even if not yet at economy-wide scale.
- The biggest risks look concentrated (Oracle, key AI labs, certain data center REITs and lenders), not systemic across the entire financial system—at least for now.
A Practical Decision Framework for the Reader
To form your own view on the AI bubble question, ask:
- Revenue vs. Debt:
Does the company’s contracted and realistic revenue support its AI-related debt load under conservative utilization and pricing assumptions? - Concentration Risk:
How dependent is the business on one or two AI counterparties or a single class of model? - Reusability of Assets:
If AI demand flattens, can its datacenters, power agreements, and hardware be repurposed for other workloads? - Market Signals:
Are CDS spreads widening? Are ratings agencies flagging leverage? Are banks increasingly hedging exposure? - Adoption Reality vs. Narrative:
Do enterprise customers show real, scaled AI adoption, or still mostly pilots, experimentation, and “AI tourism”?
9. Closing Thought: Bubble or Not, Credit Is Now the Real Story
Equity markets tell you what investors hope will happen.
The CDS market tells you what they’re afraid might happen.
Right now, credit markets are signaling that AI’s infrastructure bets are big enough, and leveraged enough, that the downside can’t be ignored.
Whether you conclude that we’re in an AI bubble—or just at the messy financing stage of a transformational technology—depends on how you weigh:
- Trillion-dollar infrastructure commitments vs. real adoption
- Physical asset durability vs. concentration risk
- Long-term productivity gains vs. short-term overbuild
But one thing is increasingly clear:
If the AI era does end in a crisis, it won’t start with a model failure.
It will start with a credit event.
We discuss this topic in more detail on (Spotify)
Further reading on AI credit risk and data center financing
Moody’s flags risk in Oracle’s $300 billion of recently signed AI contracts
Sam Altman’s Stargate is science fiction
De Lio Tech Trends 