AI infrastructure is no longer being financed only by venture rounds and public equity. Credit markets are moving in, and founders need to understand what that changes.
The AI boom is becoming a borrowing story. That may sound less exciting than model launches, chip shortages or billion-dollar valuations, but it is one of the most important changes now shaping the sector. When banks and private credit firms start treating compute, data centers and long-term customer contracts as financeable assets, the rules for building an AI company begin to change.
Morgan Stanley now expects AI-linked debt issuance to become a much larger part of the credit market, with Bloomberg Technology recently noting that AI debt is approaching 15% of the US investment-grade corporate market. The bank has also projected $250 billion to $300 billion of issuance in 2026 from hyperscalers and related joint ventures. That is not a side trade. That is institutional money building a new lane around the physical cost of artificial intelligence.
For entrepreneurs, the lesson is simple. AI may still look like a software market from the outside, but the companies scaling fastest are increasingly behaving like infrastructure businesses. They need chips, land, power, cooling, fiber, construction schedules and leasing structures. Equity alone is a difficult way to fund that kind of appetite because the amounts are too large and the dilution can become painful very quickly.
Credit investors are not lending against vague enthusiasm for chatbots. They are looking for collateral, contracts and predictable usage. That is why the most interesting deals are being built around hard assets such as GPUs, TPUs and data centers, or around customer contracts that create something close to recurring infrastructure cash flow.
The reported $36 billion financing being arranged by Apollo Global Management and Blackstone for Anthropic shows how far this has moved. According to reports citing Bloomberg News, the debt would be channeled through a special-purpose vehicle to buy Google TPUs, which would then be leased to Anthropic for data center use in states including New York, Texas, Louisiana and Indiana. Broadcom is expected to provide residual value support for roughly $31 billion of senior debt tranches, giving lenders another layer of protection if the chips have to be sold after a default.
That structure matters because it changes the conversation from whether an AI company is worth a certain valuation to whether the assets and leases can support the debt. It is a very different discipline. Founders who want to access this market will need to think more like operators of capital-heavy businesses, not just builders chasing product-market fit.
Blackstone is also moving directly into the compute layer. In May, it announced a joint venture with Google to create a US-based TPU cloud business, backed by an initial $5 billion equity commitment and a plan to bring 500 megawatts of capacity online in 2027. That is not a small experiment. It is one of the clearest signs that alternative asset managers see AI infrastructure as a long-term platform, not a short-term financing opportunity.
The risk is not disappearing
None of this means AI lending is easy money. The risk is just being priced differently. Lenders have to judge whether chips will hold resale value, whether power supply arrives on time, whether customers keep paying for compute and whether today’s model demand still exists when the debt matures. A facility backed by GPUs can look solid until the next generation of hardware changes the economics.
The OECD’s 2026 Global Debt Report puts the scale in perspective. It said private credit deals involving AI companies reached a record aggregate size in 2025, with the sector’s share of private credit deals rising from 9% in 2024 to 34% in 2025. It also pointed to Morgan Stanley estimates that private credit could supply $800 billion to the AI expansion over four years, mostly through asset-based finance structures.
Data center lending is already spreading beyond the most obvious AI names. Aligned Data Centers secured a $2.58 billion credit facility in March to support its US buildout, with the facility backed by an initial collateral pool of six assets. These are the kinds of deals that make AI financing feel less like venture capital and more like real estate, project finance and equipment leasing stitched together.
That shift has practical consequences for founders. A company with meaningful compute demand may soon have more financing choices, but those choices will come with tighter reporting, stronger covenants and closer scrutiny of unit economics. Lenders will want to know who the customers are, how long contracts run, what happens if utilization falls and what the collateral is worth in a bad market.
The opportunity is real. So is the discipline. The next phase of AI company building will reward teams that understand capital structure as well as product strategy. The founders who treat debt as a serious tool, not a rescue option, will have more room to scale. The ones who ignore the financing architecture behind the boom may find that the market has moved on without them.
Also read: AI debt is becoming a serious funding option for founders • Reid Hoffman is leaving Microsoft's board as AI scrutiny rises • New York just put AI data centers on notice
