AI investment can lift valuations and demand for financing in the near term, while successful adoption could raise productivity and ease inflation pressure over time. If earnings disappoint, stocks and planned spending may fall, and lenders may face greater exposure to AI-related debt. These forces pull in different directions: the available evidence does not support a single prediction for whether AI will raise or lower interest rates.
What counts as AI investment?
Here, AI investment means spending on the infrastructure and capacity needed to develop and deploy AI: computing equipment, data centers, and related capital expenditure. Building that capacity requires resources and financing before any productivity gains are certain to arrive.
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Using AI in financial-market trading is a separate issue. It can affect how prices are formed and how risks move through markets, but it is not the same as investment in AI infrastructure.
How does AI investment affect financing demand?
Large infrastructure projects require substantial funding. The Bank for International Settlements (BIS), in a January 2026 assessment, says the expected scale of investment will require companies to rely more on debt rather than operating cash flow alone, with private credit playing a growing role. The mix matters: taking on debt creates repayment obligations, while equity financing does not require scheduled repayment but gives investors a share in the company and its gains or losses.
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| Funding source | Repayment obligation | Transparency and who bears losses |
|---|---|---|
| Internal cash flow | No external lender repayment, but spending uses cash that could be put to other uses. | It avoids adding a new outside creditor; the company and its existing owners bear the consequences if returns disappoint. |
| Public debt, such as bonds | Interest and principal must be paid under the bond’s terms. | Public bond issuance is visible to market participants; creditors bear losses if the issuer cannot meet its obligations. |
| Private credit | Borrowers owe repayment under privately negotiated terms. | Terms and exposures are generally less visible to the public than those of publicly traded bonds; lenders bear credit losses if borrowers fail to repay. |
| Equity | No scheduled repayment of principal or interest. | Investors share in gains and bear losses through the value of their ownership stake; issuing shares can dilute existing owners. |
There is no universal cost ranking across these options: financing costs and terms depend on the company, market conditions, and deal structure. The BIS identifies a shift toward debt and a growing role for private credit, not a single funding method that dominates every AI project.
Could productivity gains lower borrowing costs?
Investment raises demand for equipment, construction, labor, and financing in the near term. If AI is deployed broadly and increases output per unit of input, it could also expand productive capacity over time. That supply-side effect may ease inflation pressure and, in turn, reduce some borrowing costs. The timing and scale depend on whether adoption produces lasting, widespread productivity gains—not just on how much is spent building infrastructure.
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Federal Reserve Vice Chair for Supervision Michelle W. Bowman said in a September 26, 2025 speech that “Investment in new technologies is likely to raise productivity and lower inflation in the medium term.” Her remarks describe a possible medium-term effect, while also recognizing that AI investment boosts demand. They are Bowman’s views and do not necessarily represent the Federal Reserve Board or the Federal Open Market Committee.
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In a September 2024 article in Finance & Development, economist Michael Spence also presented lower real rates and a lower cost of capital as a conditional possibility if AI raises productivity. That is an author’s argument, not an IMF policy position or a measured forecast of the effect of AI investment.
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How can AI affect the stock market and credit markets differently?
Equity investors value companies partly on expected future earnings. Optimistic expectations about AI-related growth can support valuations and encourage further investment. Lenders, by contrast, focus on a borrower’s capacity to repay. BIS has noted that equity prices have run well ahead of debt-market pricing, making the gap between expected earnings and lenders’ assessment of borrowers an important signal—not proof that either market has the right valuation.
If AI-related earnings fall short of expectations, share prices may be repriced and companies may cut planned investment. Lower valuations can reduce household wealth and expectations for company profits; reduced spending can also affect suppliers and economic activity. Where projects were funded with debt, lenders’ exposure matters too. Federal Reserve Governor Lisa D. Cook, speaking on May 27, 2026, said, “Broadly, I see AI as stimulating economic growth, which all else equal, should support financial stability.” This is her stated view, not a guarantee: her discussion also recognized leverage and trading-related risks.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What does AI in trading change?
AI used by financial firms can analyze information quickly and may improve price discovery and risk management in ordinary conditions. But rapid, similar decisions by multiple models can make markets harder to interpret and may amplify selling during periods of stress. The International Monetary Fund (IMF) described these potential benefits and risks in an October 2024 discussion of a chapter in its Global Financial Stability Report. This market-structure channel should not be confused with the financing required to build AI infrastructure.
The IMF reported that AI-related content made up 19% of patent applications related to algorithmic trading in 2017 and over 50% each year since 2020. Its analysis also estimated that AI-driven exchange-traded funds turned over their holdings about once a month, compared with much less than once a year for a typical actively managed equity ETF. These figures describe trading-related activity; they do not measure AI infrastructure investment or its effect on borrowing costs.
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Will AI investment raise interest rates?
There is no supported single estimate for AI’s net effect on interest rates. Near-term demand for capital and the supply of new corporate debt can put pressure in one direction; productivity gains that reduce inflation pressure could work in another. The result depends on realized productivity, the timing and scale of investment, how it is financed, and whether expected earnings materialize.
“Interest rates” also refers to different things. A central bank’s policy rate is not the same as a long-term government bond yield, a company’s borrowing rate, or a household’s mortgage or loan rate. Those rates are related, but each reflects different influences, including expected inflation, credit risk, loan terms, and market conditions. The evidence discussed here does not quantify AI’s causal effect on any one of them or provide a household borrowing-cost forecast.
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