OpenAI Anthropic Credit Ratings Face a High Bar After Their IPOs

OpenAI and Anthropic reportedly want investment-grade credit ratings immediately after their IPOs, despite the financial risks created by their enormous infrastructure plans. The push would give both companies cheaper access to debt and reduce their dependence on technology partners for financing support. However, the reported OpenAI Anthropic credit ratings campaign asks agencies to accept unusually young public companies as dependable corporate borrowers.

Morgan Stanley and Goldman Sachs have held discussions with rating agencies on behalf of the two AI laboratories, according to a September 8 report cited by financial coverage. Reuters said it could not immediately verify the original report. Neither company has publicly detailed a completed rating process.

The request is more consequential than routine IPO preparation. OpenAI and Anthropic need vast amounts of computing capacity, while their partners currently shoulder parts of the associated credit risk. Investment-grade status would let the laboratories borrow under their own names and attract a broader group of bond investors.

That possibility creates the central tension. Public listings would improve liquidity and disclosure, but neither event would automatically make future cash flows predictable. The agencies must decide whether exceptional growth offsets spending commitments, customer concentration, technology risk, and complicated financing structures.

OpenAI Anthropic Credit Ratings Have Become Part of the IPO Plan

The reported talks link two public listings directly to the next stage of AI infrastructure financing.

Investment-grade describes debt that rating agencies consider to have relatively low default risk. The category generally starts at BBB-minus from S&P and Fitch, or Baa3 from Moody’s. It matters because many pension funds, insurers, and other institutions restrict purchases of lower-rated bonds.

The banks reportedly want OpenAI and Anthropic to enter that category soon after their shares begin trading. That would be an exceptional outcome for companies still moving from private financing into public-market scrutiny. It would also turn their IPOs into balance-sheet events, not merely opportunities for shareholders to sell stock.

The logic is straightforward. An IPO can provide new cash, publicly traded equity, audited disclosures, and a market valuation. Those features can strengthen a borrower’s financial flexibility and give lenders more information.

Yet a stock listing does not eliminate operating risk. Rating agencies focus on the likelihood that creditors receive interest and principal on time. A rising share price can help a borrower raise capital, but it cannot substitute permanently for cash generated by operations.

The timing reflects the scale of the laboratories’ computing ambitions. Training and serving advanced models require chips, networking equipment, power, cooling systems, and long-term data center capacity. Developers often finance those assets before the related customer revenue fully materializes.

OpenAI and Anthropic have historically relied on equity investors and strategic partners to bridge that timing gap. Those partners include cloud providers, chip companies, private-credit firms, and infrastructure developers. Each arrangement places obligations and risks in a different part of the financing chain.

The reported rating effort would move more responsibility toward the laboratories themselves. Instead of asking a stronger partner to guarantee a project, an investment-grade AI company could support leases or issue bonds directly. That could simplify transactions and lower their total financing burden.

It could also broaden the available capital pool. Investment-grade bonds generally reach more institutional buyers than speculative-grade debt. Greater demand can improve terms, extend maturities, and reduce reliance on a small group of private lenders.

However, no rating has been announced. The reported discussions represent advocacy by bankers, not a decision from an agency. That distinction matters because investment banks benefit when large issuers gain access to more financing channels.

The companies also have different IPO timelines. Anthropic appears closer to public disclosure, while OpenAI remains at an earlier stage, according to recent reporting. A shared lobbying effort therefore does not mean both companies will receive identical ratings or reach the market together.

Their financial profiles also differ. Anthropic has emphasized enterprise adoption and cloud distribution, while OpenAI serves a broader mix of consumer, developer, and business demand. Agencies must evaluate each company separately, even when bankers present them as one new category of AI borrower.

The immediate change is therefore not a rating award. It is the attempt to make creditworthiness part of the IPO narrative before investors see every detail. That sequence puts pressure on agencies to assess unprecedented growth alongside unprecedented capital requirements.

Cheaper Debt Would Reshape AI Infrastructure Financing

Investment-grade status would transfer borrowing capacity from established technology partners to the AI laboratories consuming the infrastructure.

Data centers are expensive long-lived assets, while AI demand can change quickly. This mismatch has encouraged developers to use project finance, asset-backed loans, leases, guarantees, and special-purpose vehicles. A special-purpose vehicle is a separate legal entity created to hold assets or obligations for one project.

These structures can reduce the debt shown directly on an AI company’s balance sheet. They do not remove the economic obligation to pay for computing capacity. Credit analysts therefore examine contracts, termination rights, guarantees, and minimum purchase commitments.

The market has already demonstrated how large these arrangements can become. Apollo and Blackstone backed an initial $35 billion financing platform connected to Anthropic’s computing needs. The project was designed to support more than 20 gigawatts of capacity through 2028, according to compute financing.

That structure places hardware inside a separate vehicle while Anthropic leases access to computing resources. Broadcom and infrastructure operator Fluidstack also participate. The arrangement shows why Anthropic IPO financing cannot be understood through ordinary software-company metrics alone.

Amazon’s disclosures provide another window into the financing network. The company reported investments in both Anthropic and OpenAI, along with cloud agreements and future funding commitments. These are strategic relationships, but they also connect infrastructure demand to the balance sheets of larger companies.

Amazon disclosed a facility of up to $20 billion for Anthropic following a qualifying liquidity event. The facility becomes available as Amazon reaches specified compute-delivery milestones. Draws would take the form of convertible notes or common shares, depending on timing.

The same investment disclosure said Amazon invested $15 billion in OpenAI preferred stock during the first quarter of 2026. Amazon also agreed to purchase additional OpenAI shares under specified conditions.

Those commitments show that an IPO does not end strategic financing. Public status can activate new facilities, change the form of securities, and make additional partner capital available. A stronger credit rating would add unsecured bonds and corporate loans to that toolkit.

For infrastructure developers, the tenant’s rating directly affects project economics. A highly rated tenant gives lenders more confidence that lease payments will continue. That confidence can reduce the protections, guarantees, or extra interest required for a project.

For chip suppliers and cloud partners, the benefit is also clear. They can sell more capacity without permanently carrying another company’s credit risk. Their guarantees might shrink as the AI customer develops an independent borrowing record.

For OpenAI and Anthropic, debt offers advantages over constant equity issuance. Selling new shares dilutes existing owners. Long-term borrowing can fund assets over their useful lives while allowing shareholders to retain more ownership.

Debt also imposes discipline. Interest payments arrive regardless of whether model launches are delayed or customer growth slows. Large fixed obligations can become dangerous when infrastructure is built ahead of uncertain demand.

This is why an OpenAI investment-grade rating would matter beyond one bond sale. It could establish a benchmark for pricing leases, secured loans, and data center contracts. Suppliers might treat the rating as a substitute for some partner guarantees.

The same applies to Anthropic. A favorable rating could reduce the cost of supporting Claude’s growing enterprise workload. It could also help infrastructure developers finance projects where Anthropic serves as the primary customer.

The wider credit market is preparing for that shift. Hyperscalers issued more than $100 billion of debt during 2025, according to Western Asset. Issuance had already exceeded $165 billion by June 2026.

Its credit-market analysis estimated that hyperscaler issuance could exceed $400 billion over the following three years. The report also identified growing use of project finance and asset-backed structures across AI infrastructure.

OpenAI and Anthropic sit at the center of that expansion, but they lack the long public credit histories of Amazon, Microsoft, or Google. Investment-grade ratings would narrow that gap. They would not give the laboratories the same earnings diversity or cash reserves.

The pressure therefore falls on several groups. Strategic partners want to limit contingent liabilities. Developers want dependable tenants. Banks want more transactions. Bond investors want enough protection for risks that equity investors willingly accept.

The Rating Case Depends on Cash Flow, Not Valuation

A successful IPO can strengthen liquidity, but rating agencies must judge whether revenue can support obligations after extraordinary growth slows.

Equity investors and credit investors ask different questions. Equity buyers can accept high volatility because their upside has no fixed ceiling. Bondholders receive scheduled payments, so they focus on downside protection and repayment capacity.

A soaring valuation can help a company raise cash or issue shares during stress. That flexibility supports credit quality. However, it becomes less useful when market conditions close or the share price falls sharply.

Ratings therefore depend on durable revenue, margins, liquidity, debt levels, and contractual commitments. Agencies also examine customer concentration, competitive position, governance, and access to capital. For AI companies, model-development costs and infrastructure contracts add unusual uncertainty.

Anthropic’s reported growth strengthens its argument. Recent estimates placed its annualized revenue above $65 billion, while OpenAI said it expected annualized revenue above $40 billion. Those figures indicate that commercial demand has expanded well beyond experimental deployments.

The comparison needs caution. Recent revenue reporting noted that the two companies account for some cloud-distributed sales differently. Anthropic reportedly records the full sale before treating a cloud partner’s share as an expense.

OpenAI uses a different presentation for some comparable transactions. Neither approach is necessarily improper. Still, the distinction can inflate apparent differences when readers compare headline revenue without considering associated costs.

An IPO prospectus should provide better information. Public filings normally include audited financial statements, risk factors, related-party transactions, material contracts, and detailed accounting policies. Those disclosures would let investors examine gross margins and cash conversion alongside revenue.

That scrutiny is especially important for Anthropic IPO financing. Rapid revenue growth does not reveal how much computing expense accompanies each sale. It also does not show whether long-term infrastructure commitments remain affordable during weaker demand.

OpenAI faces similar questions. Its consumer scale creates a large distribution advantage, but serving frequent interactive requests can consume substantial computing resources. Enterprise contracts may offer steadier demand, although competition can pressure prices and margins.

Both companies also spend heavily on research, model training, security, and talent. Some costs create future capabilities, while others support current services. Credit analysts must determine how much spending remains optional during financial stress.

That distinction affects any OpenAI investment-grade rating. A company can reduce discretionary research faster than it can exit a long data center lease. Rating agencies will therefore separate flexible operating expenses from fixed or debt-like commitments.

They will also inspect liquidity after the IPO. New equity proceeds can create a substantial cash buffer. The strength of that buffer depends on offering size, existing obligations, and the speed of future cash consumption.

The companies’ strategic relationships offer both support and complexity. Amazon, Microsoft, Google, Nvidia, Broadcom, and other partners have incentives to sustain AI demand. Some are investors, suppliers, distributors, customers, or guarantors at the same time.

Those overlapping roles can improve access to capital during expansion. They can also produce circular financing concerns. A supplier might finance a customer that uses the funds to purchase the supplier’s products.

Credit agencies must identify the underlying source of repayment. If revenue depends heavily on partner-funded transactions, its quality differs from diversified cash payments by independent customers. Transparent contract terms will be essential.

Customer concentration creates another issue. A small group of cloud platforms distributes substantial AI capacity. Losing one channel could affect revenue, computing access, and financing simultaneously.

Technology cycles add further risk. Advanced chips depreciate economically when newer generations offer better performance or efficiency. A borrower can remain obligated to finance hardware that has become less competitive.

Model competition moves faster than most infrastructure cycles. Google, Meta, xAI, DeepSeek, and specialized developers can release alternatives before a data center project reaches full utilization. Open-source models can also limit pricing power for standardized workloads.

Safety incidents and regulation could interrupt demand. Governments can restrict model uses, data transfers, chip exports, or deployment in sensitive sectors. A material security failure could create remediation costs and damage enterprise trust.

These risks do not automatically prevent investment-grade ratings. Agencies routinely rate capital-intensive businesses that face regulation and technology changes. The harder question is whether the laboratories possess enough recurring demand and financial flexibility to absorb shocks.

The rating case will therefore rest on evidence unavailable in a banker’s presentation alone. Audited margins, contract duration, renewal rates, liquidity, debt-like leases, and partner exposure will determine whether growth translates into creditor protection.

Wall Street’s Promise Meets the Agencies’ Reality

The core conflict is between bankers seeking immediate market access and agencies responsible for testing repayment under adverse conditions.

Investment banks have a credible argument. OpenAI and Anthropic occupy central positions in a rapidly growing market. They have attracted strategic capital from some of the world’s largest technology companies and financial institutions.

Their products also produce real revenue. Businesses use frontier models for coding, research, customer support, document analysis, and workflow automation. These workloads can become recurring consumption rather than one-time software purchases.

An IPO would add capital and transparency. Public equity could serve as a funding source during expansion or stress. The companies might also use shares for acquisitions, compensation, and strategic transactions.

Investment-grade status could then create a more efficient capital structure. Equity could absorb business risk, while bonds fund long-lived infrastructure. That arrangement is common among mature technology companies.

The problem is timing. Most mature issuers establish public operating histories before receiving broad access to investment-grade markets. OpenAI and Anthropic want ratings while their business models, accounting disclosures, and infrastructure obligations remain in transition.

Banks may cite recent technology listings as precedents. Yet a precedent does not establish a universal standard. Rating committees must examine the specific company, security, guarantees, and cash-flow profile.

SpaceX reportedly received investment-grade ratings shortly after its 2026 listing. Its outcome gives bankers a practical example of agencies moving quickly for an unusual issuer. It also invites comparisons that may obscure important differences.

SpaceX owns mature launch operations, long-term government relationships, communications infrastructure, and physical assets. AI laboratories depend more directly on leased computing capacity and rapidly changing models. Their revenue mix and competitive cycles differ.

Even when agencies grant investment-grade ratings, bond markets can disagree. Investors continuously reprice debt after issuance. A bond initially rated investment-grade can trade at yields associated with riskier securities if buyers become concerned.

That market discipline limits the value of a symbolic victory. A rating opens doors, but it cannot guarantee inexpensive funding. Borrowing costs still respond to financial results, supply, interest rates, and investor confidence.

The cautious case begins with opacity. Both companies remain private, so outsiders lack complete audited information about margins, cash flow, commitments, and related-party transactions. Reported run rates cannot replace full financial statements.

The second concern is scale. Large infrastructure plans can turn growth assumptions into fixed obligations. If demand misses forecasts, unused capacity still requires financing, maintenance, and power commitments.

The third concern is dependency. OpenAI and Anthropic rely on partners that provide chips, cloud access, distribution, capital, and sometimes guarantees. A disruption affecting one partner can reach several parts of the business.

The fourth concern is competitive durability. Users can switch among models, route workloads across providers, or adopt cheaper open alternatives. Enterprise integrations create some friction, but the market has not yet demonstrated decades of customer stability.

The fifth concern is governance. Public investors and creditors need clear control structures, conflict policies, and decision rights. OpenAI’s unusual organizational history makes this issue especially relevant to its rating review.

None of these concerns proves that speculative-grade ratings are appropriate. They show why immediate investment-grade treatment cannot rest on brand recognition or private-market valuation. Agencies must build a defensible downside case.

Bankers can argue that refusing investment-grade status creates its own risk. Higher financing costs might increase dependence on complicated guarantees and private vehicles. Direct borrowing could make obligations more transparent.

That argument has merit, but it reverses the usual sequence. Ratings normally reflect credit strength rather than create it. Agencies would resist any claim that cheaper debt should justify the rating required to obtain cheaper debt.

The reported OpenAI Anthropic credit ratings campaign therefore tests institutional independence. Banks want access, companies want flexibility, and partners want relief from guarantees. Agencies must decide without treating those shared interests as evidence of repayment capacity.

There is also a conflict between speed and evidence. IPO schedules reward quick decisions. Credit analysis improves when agencies can review audited disclosures, final capital structures, and binding contracts.

A provisional or transaction-specific rating might bridge that gap. Agencies can assess particular securities with structural protections before endorsing the entire company as an unsecured borrower. Such an approach would keep financing available without assuming every obligation carries equal risk.

Bond covenants could provide additional protection. These contractual rules can limit new debt, require financial reporting, preserve collateral, or trigger remedies after specified events. Strong covenants could compensate for limited operating history.

Guarantees might also remain during a transition period. A partner could reduce support as the laboratory meets liquidity, leverage, or rating targets. That structure would avoid an abrupt transfer of risk immediately after an IPO.

Ultimately, the agencies’ answer will influence more than two companies. A generous decision could establish a path for other AI developers to finance infrastructure with corporate bonds. A restrictive decision would keep more risk with partners and private-credit vehicles.

Three Signals Will Decide What Happens Next

The decisive evidence will come from public filings, preliminary ratings, and the treatment of existing guarantees.

The first signal is Anthropic’s public prospectus. Recent reporting indicates Anthropic is closer to a listing than OpenAI. Its filing should reveal audited revenue, expenses, margins, cash flow, contractual obligations, and major dependencies.

The accounting treatment for cloud-distributed revenue deserves particular attention. Investors need to distinguish gross billings from the economic value Anthropic retains after partner payments. Strong retained margins would support the credit case.

The filing should also identify lease commitments and purchase obligations. Those disclosures will show whether project-level financing has kept risk away from Anthropic or merely changed its legal form. Agencies often adjust reported debt for lease-like obligations.

A detailed prospectus would strengthen the investment-grade argument if it shows recurring demand, positive cash generation, manageable fixed commitments, and substantial liquidity. Weak margins or concentrated revenue would make immediate approval harder.

The second signal is any preliminary assessment from Moody’s, S&P, or Fitch. The assigned outlook and rationale matter as much as the letter grade. A negative outlook can signal meaningful downgrade risk even when the initial rating qualifies as investment-grade.

Agency reports should explain how analysts treat strategic partner support. Explicit guarantees deserve more credit than assumptions that a large investor will intervene. Commercial importance alone does not create a legally enforceable repayment obligation.

The reports should also disclose the stress assumptions behind their conclusions. Analysts can test revenue declines, margin compression, higher computing costs, delayed capacity, and limited capital-market access. The resulting liquidity profile will reveal the rating’s resilience.

Different decisions across agencies would weaken the claim that these companies naturally belong in investment-grade portfolios. Similar decisions based on consistent financial evidence would create a stronger precedent for AI borrowers.

The third signal is what happens to partner guarantees and special-purpose vehicles after any rating. This is where the financial consequences become measurable. A rating matters most when it changes real contract terms.

If Nvidia, Amazon, Google, Broadcom, or other partners reduce credit support, risk has shifted toward the laboratories and their bondholders. That transition would confirm that the rating has independent economic value.

If guarantees remain necessary, the headline grade may overstate the companies’ standalone strength. Investors would need to determine whether they are financing OpenAI or Anthropic, a protected project, or a stronger technology partner.

Borrowing spreads offer another practical test within this third signal. Narrow spreads would show that bond investors broadly accept the agencies’ assessment. Wider trading levels would indicate persistent concern about cash flow or infrastructure obligations.

The OpenAI investment-grade rating process may take longer because its listing timetable appears less advanced. That delay could give agencies more evidence, but it could also leave OpenAI dependent on partner-supported financing during continued expansion.

Anthropic could become the first direct test. Its prospectus, rating materials, and initial debt terms would create a reference point for OpenAI. A strong reception would make the second review easier, while weak trading would encourage stricter assumptions.

Developers and enterprise buyers should care because financing costs affect product strategy. Expensive capital can encourage usage limits, longer customer commitments, or slower infrastructure deployment. Cheaper capital can support capacity, although it may also encourage overbuilding.

Knowledge workers should watch the same signals through a practical lens. Stable financing supports model availability, predictable service, and continued investment in enterprise features. Financial stress can produce abrupt changes in limits, integrations, or product priorities.

The reported OpenAI Anthropic credit ratings effort is therefore not a technical detail from the IPO process. It is an attempt to decide who finances the next generation of AI capacity and who absorbs the downside.

The immediate question is not whether either company deserves admiration for its growth. It is whether recurring cash flow can support commitments after extraordinary growth becomes ordinary. Public filings will finally give creditors better evidence.

Watch the prospectus first, the agency rationale second, and the guarantees third. Together, those signals will show whether investment-grade status reflects durable credit strength or temporarily transfers confidence from strategic partners to bondholders.