Research Eisman's argument that cloud revenue growth at Microsoft, Amazon, Google, and Oracle depends on OpenAI and Anthropic.

The public record supports Eisman’s concentration thesis most strongly as a claim about contracted future cloud growth, not as a claim about current recognized cloud revenue. Microsoft and Oracle have disclosed enough for the backlog math to be checked. Amazon and Google have not. The “70% of AI revenue / 25–35% of cloud revenue” line is a sell-side estimate he adopted, not a number any of the four companies has reported.

What Eisman actually argued

On August 12–13, 2026, Steve Eisman said research reports put OpenAI and Anthropic at about 70% of AI-related revenue at Microsoft, Amazon, Google, and Oracle, and at 25% to 35% of those companies’ cloud revenue. He also said Oracle’s roughly $600 billion backlog was about half OpenAI. His conclusion: the hyperscalers’ futures are, in effect, a bet that two loss-making labs succeed. He later said he could not independently confirm the 70% figure, but that Oracle made it “sound right.” [1] [2] [3]

The same week, Ed Zitron published a parallel argument and cited sell-side work: UBS models putting OpenAI plus Anthropic at 27% of Google Cloud revenue in 2026 and more than 48% in 2027, and Barclays putting the pair at 13% of AWS this year, rising to 18% next. Aggregated, those desks were the source of the “over 70% of hyperscaler AI revenue” line. Zitron and Bloomberg also estimated that Microsoft’s disclosed OpenAI revenue was roughly 70% of Microsoft’s own AI business. [4] [5]

That distinction matters. “AI revenue” is not a GAAP line. “Cloud revenue” is. Mixing them is how a directional research estimate became a macro claim.

What the two labs have actually promised to buy

OpenAI’s named cloud purchase commitments add up to roughly $688 billion, none of it from an OpenAI filing:

• An incremental $250 billion of Azure, contracted in the October 2025 recapitalization that left Microsoft with about 27% of OpenAI Group, valued near $135 billion. Microsoft gave up its right of first refusal on new compute. [6]
• About $300 billion of Oracle capacity over roughly five years starting in 2027, tied to 4.5 gigawatts, as reported by the Wall Street Journal. Oracle has not isolated that contract in its own filings. [7] [8]
• $38 billion over seven years with AWS (November 2025), expanded in February 2026 by another $100 billion over eight years, alongside Amazon’s $50 billion investment ($15 billion upfront, $35 billion conditional). [9] [10]

Anthropic’s contractual floors with the three clouds are smaller than the headlines, and the gap between “expected spend” and “must pay” is the whole risk. A confidential IPO prospectus seen by Reuters puts infrastructure obligations at at least $518 billion over about a decade with six partners. About 80% is non-cancelable or payable regardless of usage. The cloud floors are: [11]

• Google: $111.1 billion, April 2026–July 2033. “If our actual spend falls short, we must pay Google the difference.”
• Amazon: $110 billion, May 2026–April 2036, same shortfall clause. This matches the April 2026 announcement of more than $100 billion over ten years and up to 5 gigawatts of Trainium, paired with a fresh $5 billion Amazon investment (cumulative investment then $13 billion, with up to $20 billion more available). [12] [13]
• Microsoft: $31.4 billion, November 2026–May 2033, cancelable only for Microsoft’s uncured material breach. That sits on top of the November 2025 announcement of $30 billion of Azure capacity.
• Broadcom-linked equipment leases: $161.2 billion, largely non-cancelable. That is not cloud revenue for Microsoft, Amazon, or Google.
• xAI: up to $84.5 billion, mostly cancelable on 90 days’ notice — the exception that shows how hard the other contracts are.

In May 2026, The Information reported a separate $200 billion Anthropic commitment to Google Cloud over five years, more than 40% of the cloud backlog Alphabet had just disclosed (then a bit over $460 billion). Reuters carried that report. The prospectus minimum of $111.1 billion is a floor, not a contradiction of a larger expected-spend figure, but they should not be added together. [14] [15]

Against that bill, Anthropic’s 2025 results in the same filing are small: revenue nearly $4.6 billion (up 12-fold), operating losses above $8 billion. Consumption-based Claude usage was about $3.8 billion; subscriptions were $789 million. [16]

Backlog is where the dependence is measurable

By August 2026 the four providers’ contracted backlogs were, on Cloud Wars’ compilation of company figures: Microsoft commercial remaining performance obligations $678 billion, Oracle RPO $638 billion, Google Cloud $514 billion, AWS $496 billion — about $2.3 trillion combined. [17] Microsoft’s investor metrics confirm the $678 billion year-end figure and Microsoft Cloud revenue of $214.4 billion in fiscal 2026, with Azure and other cloud services up 41%. [18]

Microsoft is the only company that has quantified a lab’s share of backlog.

• At December 31, 2025, commercial RPO was $625 billion. CFO Amy Hood said about 45% was OpenAI — roughly $281 billion — after the $250 billion Azure commitment landed. The other 55%, about $350 billion, grew 28%. [19] [20]
• At June 30, 2026, RPO was $678 billion, up 84%. Hood said it increased 25% excluding OpenAI. Starting from the prior-year $368 billion, that implies roughly $460 billion ex-OpenAI and about $218 billion, or ~32%, still tied to OpenAI. That 32% is arithmetic from her comment, not a second direct disclosure. Either way, most of the year’s backlog growth came from one customer. [21] [22]

The same 10-K booked $24.1 billion of fiscal 2026 revenue from commercial arrangements with OpenAI, including revenue-sharing payments, and $6.0 billion of receivables from OpenAI at year-end. Microsoft had funded $11.9 billion of a $13 billion commitment. OpenAI was about 7% of Microsoft’s $331.8 billion of total revenue. Set against Azure’s first $100 billion year, the $24.1 billion is about a quarter of Azure only if all of it is compute — and the filing says it is not. [22] [23]

Oracle is the cleanest credit case, and it matches Eisman’s “half the backlog” line.

• RPO went from about $138 billion to $455 billion in one quarter in 2025, then $523 billion, $638 billion at May 31, 2026 (up 363%), and $664 billion by August 31, 2026. [24] [25]
• On July 9, 2026, S&P cut Oracle to BBB-, one notch above junk, and called OpenAI a key credit risk. S&P said OpenAI was roughly half of the $638 billion RPO. If OpenAI cannot pay, Oracle is left with data-center leases it may be unable to exit or must re-lease on worse terms. Bank of America analysts have made the same “more than half” estimate. [26] [27] [28]
• Recognized revenue tells the opposite story. Oracle has disclosed that no customer was 10% or more of total revenue in fiscal 2024, 2025, or 2026. The OpenAI contract is reported to start in 2027. Concentration is in the order book, not the income statement. [29]

The duration mismatch is the mechanism. Oracle signs 15- to 19-year building leases and long power contracts, buys the chips, and sells a roughly five-year contract to an unrated customer. Uncommenced leases were reported around $248–288 billion. Fiscal 2026 free cash flow was about negative $23.7 billion after $55.7 billion of capex. S&P projected a fiscal 2027 free-operating-cash-flow deficit near $42 billion. [30] [26]

Amazon and Google have not allocated backlog by customer. Amazon’s performance obligations, primarily AWS, reached $496 billion by June 2026. The filing identifies the $100 billion OpenAI expansion and the greater-than-$100 billion Anthropic expansion but does not say how much of the $496 billion they represent. If both are fully inside that balance, the two labs would be on the order of half of AWS’s backlog — an inference, not a disclosure. [31] [32] Google Cloud’s backlog was a bit over $460 billion in the quarter The Information used for the “more than 40%” Anthropic claim, and management later cited $514 billion. [33] [14]

A May 2026 Information analysis, carried by Reuters, said contracts involving the two labs already accounted for more than half of about $2 trillion of major-cloud backlog. Later backlog growth would dilute that share unless new lab contracts were added at the same pace. Directionally, a stack of OpenAI’s ~$688 billion of named cloud commitments plus Anthropic’s ~$253 billion of cloud floors (or ~$340 billion if the $200 billion Google figure is used instead of the $111 billion floor) is on the order of $0.9–1.0 trillion, or roughly 40–50% of a $2.0–2.3 trillion combined book. That is the quantitative core of Eisman’s argument, and it is about signed future revenue, not last year’s cloud P&L. [14]

How well the 70% and 25–35% claims hold up

Claim	What public data can actually show	Verdict
70% of the four companies’ AI revenue	No company reports “AI revenue.” Bloomberg’s ~70% is a Microsoft-only estimate: $24.1 billion from OpenAI versus an extrapolated ~$34 billion AI business. UBS/Barclays figures cited by Zitron are models.	Directional for Microsoft’s labeled AI business; not audited across four firms
25–35% of current cloud revenue	Microsoft: $24.1 billion is ~11% of $214 billion Microsoft Cloud, and ~24% of a $100 billion Azure year only if revenue-share is ignored. Oracle: no 10% customer in recognized revenue; the big contract starts in 2027. AWS/GCP: undisclosed. Barclays’ 13–18% of AWS and UBS’s 27% of Google Cloud in 2026 sit at or below the range.	Not demonstrated in current revenue. Plausible as a forward blend once take-or-pay ramps
Half of Oracle’s backlog is OpenAI	S&P: roughly half of $638 billion. WSJ: ~$300 billion contract.	Supported
OpenAI was 45% of Microsoft’s commercial RPO	Hood, December 2025 quarter, on $625 billion	Supported, as of that quarter; implied share later fell toward ~32% as other RPO grew
Two labs are ~half of combined hyperscaler backlog	Information/Reuters, May 2026, on a ~$2 trillion book. Later books are larger; customer splits at AWS and Google remain undisclosed	Supported as an estimate of contracted growth, not as a current-revenue fact

Three accounting traps make the headline percentages easy to overread.

First, Microsoft’s $24.1 billion includes revenue share. Microsoft earns when OpenAI sells to end customers, not only when OpenAI rents GPUs. Treating that line as pure cloud consumption overstates Azure dependence and understates how much of the “AI revenue” is a royalty on the lab’s own sales. [22]

Second, the labs are also distribution channels. In 2025, Anthropic routed $2.16 billion, or 47% of revenue, through Amazon and Google marketplaces, up from 11% in 2023 and 32% in 2024, and paid about $351 million back in distribution fees — roughly 16 cents per marketplace dollar. Those partners collected 60% of $909 million of customer bills outstanding. Two unnamed customers were each 12% of Anthropic’s revenue. Some “hyperscaler AI revenue” is a toll on the lab’s end customers, who are the real demand. Counting lab spend and enterprise AI spend as separate piles double-counts. [16]

Third, backlog is not cash. Oracle expects only about 12–13% of its RPO to convert within twelve months. Microsoft’s RPO duration has been about 2–2.5 years. A five-year OpenAI contract that starts in 2027 can re-rate a stock today and still not be revenue for several quarters. [28] [34]

The claim that holds is narrower and more serious than the soundbite: the incremental cloud growth that re-rated these stocks is unusually dependent on two customers. The claim that does not hold, on disclosed revenue, is that those two already are 25–35% of cloud sales at all four companies.

Circular financing and counterparty risk

The loop is the same at each node. A supplier invests equity (or hands over warrants). The lab commits to spend a multiple of that equity back on the supplier’s cloud or chips. The supplier books revenue, and often a mark-to-market gain on the equity, while the lab funds the spend with the next round. Bloomberg has mapped the pattern across Microsoft–OpenAI, Amazon/Google–Anthropic, Nvidia, AMD, and Oracle/Stargate. [35]

Specific loops that are on the record:

• Microsoft–OpenAI. More than $13 billion invested; 27% stake marked near $135 billion; $250 billion incremental Azure commitment; $24.1 billion of fiscal 2026 related-party revenue. The cash Microsoft put in is a fraction of the revenue and equity value it has booked back. [6] [22]
• Amazon–Anthropic. Ars Technica, the Financial Times, and TechCrunch all described the April 2026 deal as circular: $5 billion in (on top of $8 billion already invested) against more than $100 billion of AWS spend, much of it on Amazon’s own Trainium chips. By June 30, 2026, Amazon carried the Anthropic stake at about $190 billion, and one period’s “other income” of $53.4 billion was primarily Anthropic valuation marks. Cloud revenue and investment gains move together. [36] [37] [38] [31]
• Amazon–OpenAI. $50 billion investment, only $15 billion upfront, against a $100 billion expansion of an existing $38 billion cloud deal, including 2 gigawatts on Trainium. William Blair estimated an even spend would be about $17 billion a year, roughly 11% of expected 2026 AWS revenue — a single-customer growth slug funded in part by the vendor. [10] [39]
• Nvidia and AMD. Nvidia put $30 billion into OpenAI’s February 2026 round after a discussed commitment of up to $100 billion was scaled back. AMD agreed to buy up to $5 billion of Anthropic stock alongside more than $20 billion of expected compute supply. The chipmaker’s largest customers are also its investees. [39] [11]
• Alphabet–Anthropic. Up to $40 billion of equity, reported alongside the multi-gigawatt TPU deal, against a take-or-pay cloud floor of $111.1 billion and a reported $200 billion expected spend. [14]

Anthropic’s own prospectus states the conflict directly: Amazon, Google, and Microsoft are simultaneously investors, customers, cloud providers, distributors, and competitors, with incentives that “may not be fully aligned.” [11]

The counterparty risks analysts and rating agencies have actually named:

1. Ability to pay, not willingness to cancel. Google and Amazon minimums are take-or-pay. Microsoft’s Anthropic contract is non-cancelable except for Microsoft’s breach. The protection for the hyperscaler is only as good as the lab’s balance sheet. Anthropic’s 2025 operating loss exceeded $8 billion on $4.6 billion of revenue, against a $518 billion buildout. OpenAI’s named cloud commitments of ~$688 billion similarly dwarf any reported revenue run-rate. Both labs have to keep raising capital, or go public, for the RPO to become cash. [11] [16]

2. Oracle is the first loss-absorber. S&P’s failure path is specific: unpaid OpenAI contracts leave Oracle holding long leases and power deals it cannot easily exit. Credit markets have already priced some of that. Five-year CDS have traded at stressed levels, 2056 bonds have yielded above 8%, and debt tied to the $18 billion Project Jupiter campus has traded around 89–90 cents on the dollar. Some banks reportedly declined Stargate-linked financings where Oracle was the anchor tenant, citing concentration. [26] [40] [28]

3. Correlated marks. A price war — Eisman’s China open-weight scenario — would hit lab equity values (Amazon’s $190 billion Anthropic carrying value, Microsoft’s $135 billion OpenAI stake, Alphabet’s Anthropic marks), the collectibility of cloud RPO, and Nvidia’s order book in the same quarter. The equity upside and the cloud receivable are not independent hedges. They are the same bet, booked twice.

4. Stranded capacity is not equal across the four. S&P’s point, which Eisman has echoed, is that AWS, Google, and Microsoft have internal workloads (Search, YouTube, Gemini, Copilot, ads, retail) that can absorb unused GPUs. Oracle does not, at anything like the same scale. Microsoft’s own disclosure cuts both ways: ex-OpenAI RPO still grew 25–28%, and Azure has been capacity-constrained, so the franchise is not only two customers. But the acceleration is. [27] [20]

5. Off-balance-sheet temptation. Eisman has argued that special-purpose vehicles, guarantees, and lease structures are being used to keep AI project debt away from ratings — the incentive S&P’s July downgrade made explicit for Oracle. The economic exposure remains even when the debt does not consolidate. [41]

What this means if you are underwriting the trade

Treat backlog share and revenue share as different securities. Oracle’s equity and credit are a direct underwriting of OpenAI’s ability to fund a contract that starts in 2027 and is about half the order book, against leases that run into the 2040s. Microsoft’s risk is large but diluted: OpenAI was 45% of commercial RPO at the peak disclosure and still the majority of backlog growth, yet it was only about 7% of total company revenue, and part of the $24.1 billion is a royalty, not a GPU rental. Amazon and Google have the same circular structure, but investors cannot see the customer split; the binding evidence is the labs’ own take-or-pay floors, not the hyperscalers’ 10-Qs.

The competitive implication is uncomfortable for anyone selling cloud against these four. The incremental AI capacity is not being won in an open market. It is being pre-sold to two customers who are also financed by the sellers, on contracts that force payment even if usage misses. A third-party cloud, or a neocloud, is not competing only on price and chips. It is competing with a vendor-financed order book that already accounts for something like half of the industry’s contracted growth. The hedge inside the hyperscalers is their non-AI franchise and internal demand. The thing that is not hedged is the re-rating: if either lab’s funding window closes, the backlog that justified the capex does not disappear from the slide. It becomes a credit loss and a pile of unfilled buildings, first and hardest at Oracle.

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Recent Findings Supplement (October 2026)

Steve Eisman has reiterated and partially hedged his concentration thesis in September–October 2026 commentary, estimating that OpenAI and Anthropic together drive roughly 70% of AI-related revenue at Microsoft, Amazon, Google, and Oracle (equating to 25–35% of those firms’ total cloud revenue).[1]

This builds directly on his August 2026 statements and is supported by newly disclosed contract sizes and backlog attributions rather than broad assertions. Eisman has begun reducing exposure by shorting portions of AI holdings “against the box” while watching for price wars from open-weight models and signs that one or both labs could falter.[1]

• Anthropic’s September 2026 confidential IPO prospectus (seen by Reuters) details $518 billion in planned decade-long infrastructure spend, with ~80% non-cancellable or payable regardless of usage.[2]
• Microsoft’s FY2026 commercial remaining performance obligations (RPO) reached $678 billion as of June 30, 2026 (up 84% YoY); excluding OpenAI, growth was only 25%, implying OpenAI accounts for a large share of incremental backlog (inferred ~$217 billion+ tied to the lab).[3]
• S&P estimates roughly half of Oracle’s $638 billion backlog comes from OpenAI.[4]

This data bolsters Eisman’s core claim of heavy dependence. Public filings and reporting now quantify the scale of take-or-pay-style commitments that tie hyperscaler growth directly to the labs’ continued spending power. For competitors or entrants, the mechanism is clear: winning meaningful share requires either displacing these locked-in contracts or capturing diversified non-lab demand that is growing more slowly.

Anthropic’s September 29, 2026, IPO prospectus reveals $518 billion in AI infrastructure obligations over the next decade, including $111.1 billion with Google (April 2026–July 2033), $110 billion with Amazon (May 2026–April 2036), and $31.4 billion with Microsoft (November 2026–May 2033, non-cancellable except for material breach), plus $161.2 billion in largely non-cancellable Broadcom equipment leases.[5]

Roughly 80% of the total is structured as minimum-spend or pay-regardless-of-usage terms, giving cloud providers high visibility into future revenue but exposing them to Anthropic’s ability to fund the obligations. The company reported ~$4.6 billion in 2025 revenue against >$8 billion operating losses.[1]

• Additional details include AMD committing up to $5 billion in stock purchases and supplying >$20 billion in capacity.[2]
• Earlier 2026 expansions (e.g., >$100 billion AWS deal announced April 2026 for up to 5 GW) are folded into these aggregates.[6]

The mechanism is take-or-pay contracting that converts lab funding needs into guaranteed hyperscaler revenue streams. Implication: Any slowdown in Anthropic’s fundraising or model monetization directly pressures the clouds’ realized returns on capex. New entrants face a high bar—labs are locking in multi-year capacity with penalties for under-utilization, leaving less flexible demand for alternative providers in the near term.

OpenAI’s post-restructuring commitments include an incremental $250 billion Azure purchase obligation tied to Microsoft’s ~27% stake in the October 2025 recapitalization, a reported ~$300 billion five-year Oracle cloud deal (starting 2027, 4.5 GW), and an AWS expansion adding $100 billion over eight years to a prior $38 billion commitment.[7]

Microsoft booked $24.1 billion in revenue from OpenAI arrangements in FY2026 and reported OpenAI owing it $6 billion as of June 30; OpenAI-related deals represent a substantial portion of Azure growth and ~45%+ of Microsoft’s commercial RPO in recent periods.[3]

• Broader OpenAI compute commitments have been cited in the $600 billion–$1.4 trillion range through 2030 (with revisions noted in reporting).[8]
• Microsoft’s Azure crossed $100 billion annual revenue run-rate in FY2026, with OpenAI arrangements equating to roughly a quarter of that in some analyses.[3]

Public data therefore shows OpenAI as Microsoft’s largest single AI customer and a material driver of backlog growth across multiple providers. The circular element is explicit: Microsoft’s equity stake and financing coincide with OpenAI’s spend commitment back to Azure. For market participants, this creates concentrated counterparty exposure—OpenAI’s cash burn ($3.7 billion in Q1 2026 alone; projected heavy losses through 2030) means its ability to honor obligations depends on ongoing external capital raises.[3]

Hyperscaler backlogs and revenue forecasts now embed large contributions from the two labs, with UBS estimating OpenAI + Anthropic could account for 48% of Google Cloud’s 2027 revenue (~$84–100 billion), plus ~$40 billion at AWS and at least $50 billion at Microsoft Azure.[9]

Goldman Sachs (September 25, 2026 note) calculates the five largest U.S. hyperscalers need ~$300 billion in annual AI revenue to break even on projected 2026 AI infrastructure spend of ~$800 billion, against only ~$70 billion in current AI cloud revenue above pre-buildout levels—a ~$230 billion annual shortfall.[10]

• Oracle has raised significant debt/leases amid its OpenAI exposure; S&P links half its backlog to the lab.[4]
• Eisman and others note Nvidia’s own concentration (70% of revenue from five hyperscaler customers whose AI revenue loops back to the labs).[9]

The supporting mechanism is that capex and backlog growth are front-loaded on lab commitments whose realization depends on the labs’ solvency and usage. This strengthens Eisman’s argument with quantitative backing from filings and analyst models. For entrants or competitors, the implication is that near-term cloud/AI infrastructure demand is heavily pre-committed and concentrated; diversified or lower-cost alternatives must overcome both contractual lock-ins and the labs’ preference for established hyperscalers with financing ties.

Analysts and the Bank for International Settlements (BIS Bulletin 137, October 1, 2026) have highlighted circular-financing and counterparty risks, noting that >55% of AI funding (2021–2025) came from other AI firms, with nearly half of intra-AI deal value tied to commercial supply relationships.[11]

Examples include Microsoft’s equity in OpenAI paired with OpenAI’s $250 billion Azure commitment; Amazon/Google stakes in Anthropic alongside their large compute contracts; and chipmaker investments (Nvidia, AMD, Broadcom) that loop back as demand for their products. BIS warns these self-referential structures make reported demand partly endogenous and can amplify macroeconomic and contagion risks in stress scenarios.[12]

• Eisman has flagged Enron-like off-balance-sheet techniques and guarantees resurfacing in AI financing (September 2026).[13]
• Labs’ losses and funding dependence create direct credit exposure for hyperscalers holding the corresponding receivables and RPOs.

The risk mechanism is interconnected balance sheets where one party’s distress (lab funding shortfall or model commoditization) simultaneously hits revenue, equity values, and debt service across the chain. Public data supports Eisman’s warning: the concentration is real and quantifiable, and the circular elements introduce fragility not present in traditional enterprise cloud growth. New participants must navigate these closed loops—either by securing independent funding/customer bases or by offering materially cheaper alternatives that can pry open locked capacity. Overall, recent disclosures (especially Anthropic’s prospectus and backlog details) provide concrete numerical support for the dependence thesis while underscoring the elevated counterparty and circular risks analysts have flagged.