Cheap Money Dries Up for AI as Lenders Turn Picky

Cheap Money Dries Up for AI as Lenders Turn Picky

TREE NEWS reports: The era of easy financing for artificial intelligence companies is coming to an abrupt end. After years of raising hundreds of billions of dollars with little scrutiny, AI firms are now facing tougher terms from lenders and investors. This week, two of the industry’s most prominent players hit roadblocks: Blackstone warned investors that Anthropic is likely to receive a junk rating after its IPO, while OpenAI slashed its new funding target from $30 billion to about $20 billion. The message is clear: for the U.S. AI sector, cheap capital is increasingly hard to come by.

The News: From Easy Money to Buyer’s Market

Since ChatGPT’s launch, AI companies have tapped virtually every source of funding—venture capital, public equities, bank loans, bonds, and private credit. AI-related bond issuance in the U.S. reached $394 billion in 2025 and has already hit $655 billion by mid-October this year, with analysts expecting it to approach $1 trillion next year. But investors are growing hesitant. Concerns include rising local opposition to data centers, doubts that AI profits will materialize as quickly as promised, and fears of overexposure to the sector.

The new terms are evident across markets. Bonds from tech giants like SpaceX and Meta are trading at steep discounts. AI cloud companies such as CoreWeave, Nebius, and Nscale have effectively been shut out of the bond market in recent weeks. Even Broadcom had to offer sweeter terms to secure a loan. Anthropic, which plans to raise up to $100 billion in its mid-November IPO, was told by Blackstone that it is more likely to receive a BB-range rating—speculative grade—rather than the investment grade it had hoped for. That would narrow its funding channels and raise costs, as many insurers and pension funds are restricted from holding large amounts of junk debt.

OpenAI faces similar pressures. It has cut its funding target to about $20 billion and lowered its valuation from $1.4 trillion to $1.25 trillion. Some investors have reduced their subscriptions, and others are waiting to see how Anthropic’s IPO performs.

Market Impact: Stocks, Bonds, and Beyond

The implications are broad. For equities, the AI trade is losing its cushion. On Thursday, Alphabet lost about $500 billion in market value—the largest single-day drop in history—and Intel plunged 29% on Friday. The Nasdaq Composite fell 2.9% on Friday, marking one of the largest selloffs since the AI boom began. If volatility persists, financing will only become harder, creating a negative feedback loop.

In credit markets, the stress is most acute among “neocloud” companies—AI infrastructure providers that often evolved from crypto miners. CoreWeave’s bonds, issued earlier this year at a 9.75% coupon, now yield over 15% in the secondary market, signaling a sharp rise in borrowing costs. The high-yield market for new neocloud issuance is effectively closed. Even investment-grade tech giants are not immune: their bonds are trading at near-historic low prices, with yields notably higher than the average investment-grade corporate bond.

The pain extends to private markets and IPOs. Lambda cut its pre-IPO valuation from $14.5 billion to $13 billion after some investors balked. Nscale is considering delaying its IPO to December and may struggle to reach its $30-35 billion valuation target. For crypto, the impact is indirect but real: mining companies that pivoted to AI hosting are finding it harder to fund expansion, which could slow the buildout of decentralized compute networks and AI-crypto hybrids.

Commodities and currencies are less directly affected, but the AI investment cycle has been a marginal driver of demand for electricity, copper, and other inputs. A slowdown in data center construction could weigh on those markets. The dollar, meanwhile, remains supported by tight monetary policy, but if AI capex slows, it could dampen U.S. growth expectations.

Why It Matters: The Reflexivity of AI Financing

The shift is structural. AI buildout is increasingly reliant on external funding. The five biggest hyperscalers—Microsoft, Alphabet, Amazon, Meta, and Oracle—are expected to spend more on capex than they generate in free cash flow by 2027, with $1.57 in new capex for every $1 of operating cash flow. They cannot stop investing due to a “prisoner’s dilemma”: if one pulls back while rivals keep spending, it risks falling behind.

As investor Citrini noted, this changes the nature of risk. In the first three years of the AI trade, sentiment-driven selloffs had a floor because most spending came from hyperscalers’ operating cash flow. Now, incremental spending is funded by equity and debt. If sentiment turns, that incremental money can dry up. This reflexivity—where confidence supports financing, financing supports investment, and a loss of confidence reverses the cycle—is the key vulnerability.

For investors, the message is to watch credit markets closely. The cost of capital for AI is rising, and the weakest links will feel it first. Companies with strong balance sheets can still access funding, but patience is thinning. The AI trade is no longer just about growth; it is about who can finance it.

Key Takeaways

• Cheap funding for AI is ending as lenders demand stricter terms and higher returns.
• Anthropic faces a likely junk rating, and OpenAI has cut its funding target, signaling a broader shift.
• AI-related stocks and bonds sold off sharply this week, with Alphabet losing $500 billion in market value.
• Neocloud providers and crypto-mining-turned-AI companies are most vulnerable to rising borrowing costs.
• Investors should monitor credit markets and the reflexivity between sentiment, financing, and AI capex.