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The Artificial Intelligence boom is starting to create a new opportunity for U.S. regional banks with sizable commercial and industrial lending businesses.
While large Wall Street banks have already taken a major role in financing data-center growth, regional lenders are benefiting from the companies operating further down the supply chain.
Demand for C&I loans has increased in the second quarter, with a net of 16.1% of banks reporting stronger demand from large and midsized companies, up from 4.8% in the previous one, according to the Federal Reserve’s Senior Loan Officer Opinion Survey.
Bank loan officers said this is because companies are looking for more credit to finance their plants and get more inventory.
J.P. Morgan also found that we are experiencing an AI infrastructure boom, with data showing hyperscaler capital expenditure is projected to reach $697 billion in 2026, as more cloud providers and tech companies increase their spending on data centers and related projects.
“AI financing is the biggest secular theme in our professional lifetimes,” said John Servidea, global co-head of Investment Grade Finance at J.P. Morgan.
That spending has also made its way to the wider economy and Wells Fargo analysts are calling it a “trickle-down” from AI infrastructure investment, with demand growing towards electrical equipment, power generation, natural gas and other construction materials.
How Regional Banks Are Plugging Into the AI Financing Boom
Some regional lenders are finding ways to participate in the AI surge without taking on the same level of risk as the largest Wall Street Banks, while others are becoming direct lenders to data center developers.
In April, First Citizens Bank acted as an admin agent, joint lead arranger and bookrunner on a $525 million financing deal for T5 Data Centers, including support for a new 36-megawatt facility in Chicago and expanding one in Charlotte.
The firm has also financed other similar projects in the AI and data space such as its $650 million investment in Vantage Data Centers, $1 billion in Cologix, $930 million in Edged and $800 million in EdgeConneX.
Citizens Bank also led a banking syndicate in June alongside PNC, U.S. Bank, Regions and other lenders to help DataBank construct its Red Oak, Texas Campus facilities.
But not every regional lender is using the same direct strategy. PNC executives, for example, said on their second-quarter earnings call that it had no major exposure to data-center construction loans.
The same can be said about Fifth Third, which indirectly supports AI data center construction by providing loans to companies that supply them with concrete, aluminium, HVAC systems and other relevant services.
AI Capital Rotation is Shaping Funding Conditions
A Wall Street Journal (WSJ) report found that individual traders and hedge funds have been moving away from Bitcoin and other cryptocurrencies in favour of AI stocks.
The flow of capital into AI is creating a new funding dynamic for regional banks, as stronger investor demand for the sector could increase borrowing needs while intensifying competition among lenders. Banks looking to capture AI-related loan growth may have to compete more aggressively for borrowers and offer sharper pricing, potentially putting pressure on loan yields.
The rotation is also changing where crypto-linked infrastructure companies see opportunities. Bitcoin miners have been on the move lately, and more of them have been looking into converting their existing power bandwidth and data-center infrastructure into AI computing facilities.
Riot Platforms, for example, recently agreed to provide 191 megawatts of its capacity to AI firm Anthropic under a 20-year $9.1 billion agreement. Hut 8 has taken a similar route, securing a 15-year $9.8 billion lease for 352 megawatts of AI data-center power at its Beacon campus.
Bitcoin mining stocks have also benefited from the shift in 2026, and data from on-chain analyst Maartunn showed that Riot Platforms had gained 83% year to date while Hut 8 was up 72%.
For regional banks, however, greater demand does not necessarily mean better returns. Lenders will need to manage concentration risk and carefully assess whether AI-related projects can generate enough cash flow to support long-term debt, especially if competition pushes pricing lower.
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