The bill for the prosperity of AI may be paid by non AI companies. I recently read an article by Sentora CEO Anthony DeMartino titled 'The Debt Supercycle Is Here, and So Is the Opportunity It Creates'. The article proposes a noteworthy perspective: The competition in AI has shifted from algorithms and chips to the stage of heavy asset construction. Data centers, chip factories, power grids, and energy infrastructure require trillions of dollars in investment. Morgan Stanley predicts that global data center construction will require approximately $2.9 trillion by 2028, of which $1.5 trillion cannot be covered solely by tech giants' own cash flows and will need to be financed through corporate bonds, asset securitization, and private equity lending. This may create a conductive chain: AI companies raise large amounts of financing → Increased supply of bonds and long-term assets Institutional funds tilt towards AI infrastructure Market term premium and other rising financing costs for enterprises → Some high-quality borrowers with smaller scale and shorter terms are ignored The Dallas Federal Reserve estimates that the duration supply of AI related investment grade bonds in 2026 may reach about one eighth of the duration supply of US treasury bond bonds in the same period. Even if AI companies do not directly "snatch" loans from other companies, such a large financing demand may change the pricing of the entire credit market. The opportunity seen by Sentora is to use stablecoin funds to support fintech borrowers that have been overlooked by traditional institutions, such as payments, remittances, salary advances, and digital banking companies. These loans usually have shorter terms and are repaid by accounts receivable or cash flow, which can generate higher returns for fund providers than ordinary deposits. This logic is very enlightening, but it needs to be viewed in two parts. The macro part is relatively credible: the wave of AI infrastructure financing may indeed push up capital costs and reshape the relative pricing of credit markets. The product part still needs to be verified: short term does not mean low risk, and "self repayment" does not mean no default. Fintech loans may still face issues such as accounts receivable fraud, duplicate pledges, regulatory changes, service provider closures, and liquidity mismatches. Combined with stablecoins, smart contracts, custody, and legal enforcement risks, high returns are not created out of thin air by blockchain. To be more precise: Stable coin private equity credit income =Risk-free interest rate Credit risk compensation Liquidity compensation Structural complexity compensation On chain risk compensation Costs and actual losses So, the viewpoint that is truly worth considering in this article is not 'a stable coin profit product is worth buying', but rather: AI capital expenditures may become one of the most important pricing forces in the global credit market in the coming years. When funds chase trillion dollar AI projects, a group of small borrowers who are unrelated to AI and have decent fundamentals may be repriced. Being able to identify the 'wrongly killed credit' among them may generate new investment opportunities. But the opportunity lies not in the three words' stablecoins', but in the credit quality, collateral structure, legal rights, and risk pricing of underlying assets. Original text: https://(sentora.com)/research/articles/the-debt-supercycle-is-here-and-so-is-the-opportunity-it-creates Research on AI Private Equity Credit Stablecoins RWA Credit Market Investment