The talk in every AI Telegram group this week should not be about model benchmarks. It should be about a quiet line buried in a Financial Times report published on September 8: bankers for OpenAI and Anthropic have started pushing rating agencies for top-tier credit grades, tied to an IPO that neither company has actually confirmed.
OpenAI is reportedly sitting on roughly $3.4 billion in annualized revenue. Anthropic has pushed past the $1 billion mark. Yet the two biggest names in frontier AI are still burning through capital at a rate that would make a DeFi treasury manager wince. And now their investment banks are doing something that feels almost like a joke: asking credit agencies to bless these capital-hungry laboratories with the highest possible ratings.
From the front lines of the hype cycle, I can tell you this is not a story about an IPO. It is a story about what comes after the IPO. It is about the bond market becoming the next AI battlefield.
The companies themselves have not confirmed a timeline. Standard & Poor's, Moody's, and Fitch have not published an AI-specific rating methodology. That has not stopped the banks from pushing. In finance, "push" is a very deliberate word. It means someone at the table is resisting. It means the bankers are not asking politely. They are trying to sell the rating agencies a narrative that no pure software company has ever been asked to sell before: a story about a loss-making AI lab that deserves access to some of the cheapest debt in the world.
Why the Rating Push Matters More Than the IPO Rumors
Consider what a credit rating actually is. It is not a stamp of technological approval. It is an assessment of whether an organization can pay back borrowed money. A company with a top-tier rating can issue bonds at rates around 4-5 percent. A company that has to rely on private equity rounds is, in effect, paying an implicit capital cost of 15-25 percent if you measure the dilution and expected returns demanded by venture investors.
The difference between those two numbers will decide who wins the AI race over the next decade.
OpenAI and Anthropic are no longer at the stage where they can fund a multi-billion-dollar compute roadmap through equity alone. They need to do what Microsoft, Google, and Amazon did decades ago: build a capital structure that lets them borrow cheaply against future cash flows. The rating push is the first public signal that both companies are preparing for that transition.
The timing matters. Rating agencies do not like surprises. They prefer to see six to twelve months of financial history before assigning a serious grade. If the bankers were only waiting for an IPO before starting these conversations, the rating would not arrive until long after the public listing hype faded. The fact that conversations are happening now means the banks are already modeling the post-IPO balance sheet. They want the rating in place before the first major bond deal, not after.
The deeper signal is that OpenAI and Anthropic are moving from an era of pure equity dependence into an era of blended finance. In the crypto world, I spent years watching protocols inflate their treasuries with token emissions only to discover that liquidity is not the same as capital discipline. The same lesson is now arriving in AI.
A credit rating forces discipline. It forces companies to answer questions about gross margins, customer concentration, cash flow visibility, and governance. These are questions that venture-backed AI labs have been able to avoid because their investors have been willing to accept narrative in place of earnings. Rating analysts will not accept that trade. They want to see contracts, renewal rates, and unit economics.
That is why this news is more important than any single model release. It signals that the AI industry is being dragged into a financial framework designed for companies with predictable revenue. The era of measuring AI success purely by parameter count is ending. The new era will measure capital efficiency.
The Core Signal Nobody Is Discussing
The real signal here is not the IPO. It is the capital structure.
OpenAI and Anthropic are telling the market, in the language of investment bankers, that their business models have matured enough to survive public scrutiny. OpenAI is following the playbook of a platform company: aggressive unit cost reductions, falling token prices, and a widening ecosystem. Anthropic is following a different path, closer to enterprise software: premium pricing, safety as a moat, long contracts with regulated industries, and a stated commitment to reliability over speed.
Those two different strategies will produce two very different credit narratives.
OpenAI can point to the declining cost per token across its model lineup as evidence of structural margin improvement. It has built a consumer channel, a developer channel, and an enterprise channel. Its growth trajectory is volatile but massive. A rating agency that believes in OpenAI's ability to keep riding the scaling curve will see a story similar to a high-growth cloud software company.
Anthropic has a different sales pitch. It has designed its offerings for financial institutions, healthcare organizations, and law firms—customers who care more about predictability than price. That translates into longer contracts, fewer churn risks, and higher average revenue per customer. But it also caps the growth curve. Anthropic's rating narrative is closer to a SaaS credit model with a premium quality angle.
Yet there is a problem hiding inside both narratives: dependency.
OpenAI leans on Microsoft for cloud capacity, distribution, and a strategic investment that has become existential. Anthropic leans on Amazon and Google for compute, capital, and distribution. Rating agencies normally see strategic investors as a source of support. But when the strategic investor is also the supplier, the cloud vendor, and the primary route to customer acquisition, the relationship starts to look like concentrated counterparty risk.
If Microsoft decides that its contractual commitment to OpenAI is no longer strategically aligned with its own AI ambitions, what happens to OpenAI's revenue projections? If AWS raises prices or tightens terms, what happens to Anthropic's gross margin? These are not abstract questions. They are the questions every credit committee will ask.
From my experience auditing DeFi protocols, I saw the same pattern in liquidity pools: a project with one dominant capital provider never really controls its own balance sheet. The dependency looks like support until the moment the sponsor changes strategy. Then it looks like a cliff.
Chasing the alpha, one block at a time, means asking who controls the key variable. In AI, the variable is no longer solely the model. It is the cost and security of the cloud relationship behind it.
There is also a harder question: how do you rate a company whose most valuable assets are its researchers?
In traditional credit analysis, key-person risk is a footnote. In frontier AI, it is central. The ability to ship the next frontier model depends on a small number of elite researchers with deep expertise in a field that did not exist a decade ago. Rating agencies have no historical framework for that. They cannot look at twenty years of audited financial statements. They have to look at a bench of engineers and scientists whose departure could materially change the forecast.
The situation becomes even more confusing when the company's stated mission—particularly Anthropic's Public Benefit Corporation structure—prioritizes safety over shareholder returns. A traditional rating analyst might read that mission as discipline. A mission-driven company may be less likely to take reckless financial risks. But it may also be less willing to sacrifice safety research to protect quarterly earnings.
And then there is the wildcard: the rating agencies themselves. They are being asked to assess companies that are still losing money, have no equivalent precedent, and operate in a market where the competitive landscape can shift every six months. There is no rating methodology for general-purpose artificial intelligence. The agencies will have to invent one from scratch. If they treat AI technical risk the way they treat cybersecurity risk, the first top-tier rating will be very conservative. If they treat AI safety as a governance issue, OpenAI's history of safety-team departures will not help its case.
The bankers who pushed this story to the Financial Times know all of this. They also know that a rating is not just an opinion. It is a positioning device.
The Contrarian Angle: This Is Probably About Negotiation, Not Debt
Here is the uncomfortable truth that most analysts are missing: a rating push before an IPO is also a weapon for private-market negotiation.
Imagine you are a sovereign wealth fund considering whether to buy shares in one of these AI companies at a $200 billion valuation. The company can do one of two things. It can tell you about its technology roadmap. Or it can tell you that its bankers are already in talks with credit rating agencies for a top-tier grade. The second message is louder. It says the company is strong enough to walk away from private money and access public debt markets. It says valuation demands must be reasonable before the public market resets the reference point.
Many reporting narratives assume the rating push is step one toward an imminent IPO. A more cynical read is that it is a strategic signal meant to strengthen the company's hand in private fundraising, employee retention conversations, and compute procurement deals.
The phrase "push" in the FT report is significant. If rating agencies were already comfortable assigning top grades, the word would be "secure." Instead, bankers are pushing. That implies resistance. That implies the credit agencies are asking questions the banks are struggling to answer: Where is the profit? What is the moat? What happens if open-source models erode your pricing power in the next 18 months?
A top credit grade would require the agencies to believe that AI model leadership can be converted into durable, predictable cash flow. No company has ever proven that in an AI context. OpenAI and Anthropic have proven they can attract users. They have not yet proven they can maintain pricing power in a market where model costs are collapsing and open-source alternatives are improving at a frightening pace.
Maybe the bankers are not really targeting AAA or AA. Maybe they are simply softening the ground so that the first official rating—even if it lands at A-minus—looks like a conservative initial grade with room to upgrade. That is standard practice in the bond markets. Start with a defensive rating, let the company grow into it, and capture an upgrade story later.
Here is another blind spot: the banks that are pushing the ratings are the same banks that would earn massive fees from an IPO and a debt issuance. The story leaking to the press conveniently feeds the excitement that makes those fees possible. In crypto, I learned that when an auditor is paid by the project being audited, the audit is a marketing document. The same incentive distortion exists in the world of rating pre-engagement.
There is also a more technical path that no one is discussing. OpenAI and Anthropic do not necessarily need an issuer rating to access debt capital. They could borrow against their computing assets directly. Nvidia GPUs retain value. Data centers can be structured as collateral. A subsidiary could issue bonds backed by hardware leases or compute contracts without forcing the parent company to go through a messy corporate rating process.
The "asset-level" approach is common in traditional energy and infrastructure finance. It has not yet become common in AI, but the logic is the same: lend against the hard asset, not against the uncertain enterprise cash flow. The fact that the banks are talking about entity-level ratings instead of asset-level structures suggests they want something bigger and more strategic—or they are deliberately overselling to make the eventual compromise look reasonable.
Pivoting when the chart says pause is what separates patient investors from hype chasers. The chart here says pause.
The Stock Market Is Not the Endgame
When I look at this story through the lens of eleven years of watching capital cycles, the most important takeaway is not whether OpenAI or Anthropic files an S-1 in 2025 or 2026. The important takeaway is that the AI industry is about to be governed by a new kind of clock.
IPO and credit rating teams operate on quarterly disclosure cycles. They expect precise financial reporting. They expect budgets for compliance, audit, internal controls, and risk management. They do not move at the speed of a Discord server or a scientific breakthrough. The AI industry, which has been accustomed to moving faster than everyone else, is about to be forced into a slower material.
The shift will ripple through the entire ecosystem. Smaller AI companies will be measured against the public financial disclosures of OpenAI and Anthropic. Venture investors will have a benchmark for what AI revenue quality should look like. And if the two largest AI labs can access debt at 4 percent while their smaller rivals still rely on 20 percent equity capital, the gap between first-tier and second-tier AI companies will become a chasm.
Credit ratings, oddly enough, will become one of the most important AI moats of the next decade. The resources needed to train and deploy frontier models are no longer just a technical constraint. They are a balance-sheet constraint.
The question investors should ask is not when those IPOs will happen. The question is whether the ratings agencies—with their conservative models and their deep distrust of unproven cash flows—will ever look at an AI lab and see a durable business rather than a research project with a very expensive hobby.
Every red candle in the AI trade's future will be a lesson about that gap between technological ambition and financial reality. The sprint never stops, only the pace.
Watch for three signals. First, an actual S-1 filing. Second, the publication of any AI-specific credit rating methodology by one of the three major agencies. Third, any unsolicited rating assessment. If none of those appears within six months, treat this FT story as an invitation to negotiate, not an invitation to invest.
The bond market is the next fighter in the AI race. The bankers are placing their chips. The ratings agencies are holding the cards. And the only thing that is certain is that speed is no longer the only currency that matters. Credit is the new frontier—and the party is just getting started.