Venture investor says Goldman and JPMorgan are morphing into “AI stocks” as banks fund the buildout

A venture capital executive says some of Wall Street’s biggest banks are starting to look less like traditional lenders and more like investors in artificial intelligence, as banking financing becomes a key enabler of AI infrastructure and deployments. PSP Growth’s Momei Qu, in a commentary reported by Yahoo Finance via a syndicated post, said Goldman Sachs and JPMorgan Chase are becoming “AI stocks.” The characterization hinges on the idea that banks are not just servicing AI customers, but are also financing the broader investment cycle that supports AI buildouts, including data-center expansion, chip-related supply chains, and enterprise adoption. Qu’s argument, as presented in the post, is that AI is increasingly funded through financial channels, not only through venture capital and technology budgets. In that framing, banks gain exposure to AI-driven capex and working capital needs, even if they do not take direct operational control of AI systems themselves. The result, the executive implied, is that investors may start viewing certain banks as proxy beneficiaries for AI spending trends. While the claim is framed as a market read rather than a corporate disclosure, it also reflects a broader shift in how investors evaluate banks’ revenue drivers. Traditional bank metrics still matter, but they can be complemented by narratives about where credit demand and capital markets activity are heading, particularly when a single spending theme dominates across multiple industries. For JPMorgan Chase specifically, the business model includes a wide range of activities that can intersect with AI financing needs, from corporate lending to capital markets services. However, the cited post does not provide JPMorgan-specific disclosures, AI-related deal counts, or financial guidance tied to AI. As a result, the “AI stock” framing should be understood as an interpretation of financing dynamics rather than evidence of a measurable, newly reported AI revenue line at the company. Goldman Sachs is addressed in the same way in the post, with Qu’s view pointing to the banks’ capacity to support and accelerate transactions tied to AI. The commentary does not attribute any particular announced contract, partnership, or project to either bank, and it does not quantify exposure to AI-related lending or underwriting. Still, the idea that banks can serve as financial pipelines for AI investment is consistent with how large-scale technology programs typically progress. Enterprises often require substantial upfront funding, and AI rollouts can involve long lead times for compute, storage, and infrastructure. Banks, especially major global institutions, can be positioned to intermediate those requirements through multiple products, from credit facilities to underwriting services. The key uncertainty is how much of this “AI stock” narrative translates into bank financial performance versus how much remains a sentiment-driven re-rating. Without JPMorgan or Goldman providing new AI-specific metrics or disclosures, it is not possible to determine from the post alone whether AI financing will materially change margins, credit losses, or earnings composition. What to watch next is whether either bank highlights AI-linked demand in investor communications, or whether regulators and analysts track changes in lending and capital markets activity tied to AI capex and infrastructure.