AIR Platforms’ Oct. 1, 2026 analysis assigned OpenAI a BB+ shadow rating and Anthropic a BBB shadow rating. In conventional credit-rating terminology, BB+ is the highest speculative-grade notch—often called “junk”—while BBB is the lowest investment-grade category. These are AIR’s modeled assessments, not ratings issued by Moody’s, S&P, or Fitch, and neither grade establishes that an agency has rated either company.
What the ratings say—and what they do not
AIR’s comparison places OpenAI one notch below investment grade and Anthropic at its lowest investment-grade level. The labels describe AIR’s own analysis, not a formal agency decision. AIR states that it is not registered with the U.S. Securities and Exchange Commission as a nationally recognized statistical rating organization (NRSRO), and that its ratings, credit scores, and assessments are not issued by an NRSRO. AIR’s analysis and disclosure are the primary source for the grades.
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The distinction matters because an agency rating is an independent credit opinion issued under that agency’s process; AIR’s figures are shadow ratings produced using its own modeling approach. Separately, Semafor reported on Sept. 8, 2026 that bankers for the companies were reportedly seeking investment-grade ratings ahead of possible IPOs. That report concerns prospective requests, not ratings that agencies had already issued.
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AIR says its Financials Builder is designed to assess companies without published financial statements. It combines risk profiles, available financial information, sector characteristics, and selected peer-company data to estimate proxy financial statements. Users can change the peer group and override estimated values before the tool produces what AIR calls a first-pass approximation of private-company creditworthiness.
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That makes the result sensitive to the quality of the available inputs and to assumptions about comparable companies. AIR’s published article does not reveal enough of the underlying estimates and calculations for an outside reader to reproduce either grade independently.
OpenAI: losses and limited interest coverage weigh on the result
AIR identifies estimated losses relative to revenue and limited interest coverage as the main factors pulling OpenAI’s grade down. It says leverage was not extreme and the estimated asset mix was relatively liquid, but those factors did not offset the income-statement weaknesses. AIR says the difference between the two companies’ ratings comes almost entirely from the income statement.
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Anthropic: a near-breakeven quarter supports a conditional BBB
For Anthropic, AIR says it used reported second-quarter revenue and an operating result around breakeven, alongside its earlier estimates for assets and debt. AIR describes interest coverage as very high, but flags profitability as the main weakness. Its BBB result relies on a single reported quarter near breakeven; one quarter does not establish that the company can sustain that performance.
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AIR says the financial figures in its article are blurred and directs readers seeking details to contact its representative. The disclosed information therefore does not provide a complete, independently checkable set of inputs for the Anthropic calculation.
What could change the credit picture
IPO proceeds could improve liquidity, not prove profitability
AIR says its shadow ratings do not include proceeds from the companies’ planned IPOs. If an IPO raises primary-share capital, the resulting cash and equity could ease funding or refinancing pressure. But new capital would not, by itself, eliminate operating losses or demonstrate stronger interest coverage. The IPOs’ timing, size, and pricing were uncertain in AIR’s analysis.
Audited statements could replace estimates
Published audited financial statements could replace some of the estimated and peer-imputed figures in AIR’s model. Better disclosure might move either rating up or down; it is not automatically positive if verified results differ from the estimates.
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Why a lab’s debt cannot be judged in isolation
The headline grades focus on each company, but AI financing can involve a wider set of obligations and counterparties. UBS Asset Management describes an interconnected financing network spanning AI labs, cloud operators, data centers, compute suppliers, guarantees, leases, and other commitments. A broader credit assessment should therefore consider who owes what to whom, and which contractual support or obligations connect those parties—not only an issuer’s headline debt figure.
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How to read the comparison
- Operating performance: Look at profitability and cash generation relative to interest expense. AIR’s stated explanation centers on these income-statement measures.
- Liquidity and leverage: Cash-like assets and debt levels can affect a company’s ability to meet obligations, but AIR says OpenAI’s comparatively favorable liquidity and leverage characteristics did not erase its operating weaknesses.
- Disclosure quality: Estimated proxy statements and adjustable peer assumptions carry more uncertainty than complete, audited company statements. AIR’s published figures are not sufficient to reconstruct its calculations.
- Network exposure: Leases, guarantees, commitments, and counterparties may create credit exposure beyond the company named in a rating headline.
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