# What bubble? JPMorgan says the $5.5 trillion AI capex explosion is profitable–for now > Source: > Published: 2026-06-25 09:47:57+00:00 JPMorgan Global Research is doubling down on a central thesis for 2026: the surge in AI investment is not only durable, but increasingly profitable. In its midyear outlook, the firm points to a broadening capital expenditure cycle anchoring growth expectations. At the center is the “AI upstream” buildout—data centers, chips, and supporting infrastructure—still heavily concentrated in the U.S., which commands about 85% of AI and machine learning venture capital. Spillover benefits are expected in China, South Korea, and Taiwan, given their roles in semiconductor supply chains. JPMorgan now estimates total global AI-related capital expenditures will reach $5.5 trillion through 2030, up from $5.1 trillion. The increase reflects higher capacity expansion and a shift in financing. The bank raised its estimate for debt financing tied to the AI buildout to $4.1 trillion, citing higher loan-to-cost ratios. But the scale of spending can raise questions about whether AI demand will grow quickly enough to justify the capacity being built. While cloud providers such as [Amazon](https://fortune.com/2026/06/24/amazon-web-services-ceo-matt-garman-bullish-on-entry-level-gen-z-talent-hiring-thousands-interns-graduates/) [Google](https://fortune.com/2026/04/29/google-earnings-cloud-ai/), and [Microsoft](https://finance.yahoo.com/markets/stocks/articles/microsofts-ai-revenue-run-rate-164700434.html) report rising AI revenue, investors still remain divided on how long it will take for returns to match investment levels. Regarding financing conditions loan-to-cost ratios average above 85%, with some exceeding 90%, reflecting both favorable credit conditions and perceived value creation. In some cases, investors are assigning outsized equity value to expansion—for example, a $15 million-per-megawatt investment translating into a $25 million increase in market capitalization. Hyperscalers—the primary drivers of AI infrastructure spending—appear to be entering this phase from a position of strength. JPMorgan expects their capital expenditures to reach $650 billion in 2026 and exceed $1.1 trillion in 2027. Profitability remains intact, with operating cash flow projected to surpass $900 billion by 2027. Still, the investment cycle remains concentrated among a small group of technology companies, meaning any slowdown could have an outsized impact on industry growth. Recent equity issuance is reinforcing balance sheets. Analysts suggest elevated leverage reflects a strategic choice: companies are financing projects with debt while conditions are favorable, preserving flexibility to deleverage later. Credit markets will play a pivotal role. JPMorgan forecasts high-grade corporate debt will account for more than $2.1 trillion in data center financing over five years. In 2026, the bank anticipates $150 billion in U.S. hyperscaler issuance and another $100 billion equivalent abroad. Additional financing—about $170 billion—is expected from data center and chip issuers outside the core high-grade market, though alternative channels will remain relatively small. For JPMorgan, the conclusion is clear: AI-driven capital spending is scaling rapidly, and the economics are holding, for now. It will still be closely watched whether adoption will keep pace with the trillions being invested. **Subscribe to Fortune Gulf Brief**. Every Tuesday, this new newsletter delivers clear-eyed, authoritative intelligence on the deals, decisions, policies, and power shifts shaping one of the world’s most consequential regions, written for the people who need to act on it.