AI chip boom may outlast 2028, ASML CEO says, as Broadcom flags potential financing bottleneck

Artificial intelligence is keeping the semiconductor equipment and infrastructure buildout moving, even as executives debate how long the current spending cycle will last. ASML Chief Executive Christophe Fouquet said the AI-driven chip boom could extend beyond 2028, pointing to ongoing demand for leading-edge manufacturing capabilities that support advanced chips.

In remarks carried by Yahoo Finance, Fouquet framed the outlook around continued needs for more sophisticated chip production. ASML is the dominant supplier of key process equipment used to fabricate advanced logic and memory at small feature sizes, making its order flow a close read on the pace of global wafer-fab investment.

Broadcom Chief Executive Hock Tan, speaking in the same theme, cautioned that the industry’s biggest obstacle may not be demand itself, but the ability to fund it. In Tan’s view, the availability and cost of financing could constrain how quickly customers and suppliers can expand capacity and sustain capital spending through the next phases of the AI cycle.

The financing question matters because AI buildouts are capital intensive across multiple layers, including semiconductor manufacturing, advanced packaging and testing, and the data center networking and server supply chains that house the chips. Even when demand is strong, companies often rely on financing terms, balance sheet capacity, and project-level underwriting to move projects from planning to execution.

Taken together, the comments highlight a split focus common in the AI hardware conversation. Equipment leaders like ASML tend to emphasize how long production demand will require new manufacturing throughput, while infrastructure suppliers and chip designers often focus on whether supply chain partners can secure the funding needed to translate long-term demand into near-term capacity.

For Broadcom specifically, the implication of Tan’s warning is that ecosystem stakeholders could reach a point where capital access, risk appetite, or cost of funds slows expansion, regardless of whether end-market demand remains firm. That could affect customer timelines for data center deployments and the sequencing of orders for components and manufacturing services.

What is not clear from the Yahoo Finance report is how broadly Tan meant the financing bottleneck, or whether it would primarily hit semiconductor manufacturers, component suppliers, or data center operators. The post also did not specify any quantitative thresholds, timelines, or scenarios for how financing conditions could change the pace of AI-related spending.

Investors and industry watchers will likely watch for follow-on indicates from major semiconductor equipment orders, data center capex guidance from large cloud and enterprise customers, and any new commentary from AI hardware suppliers on whether financing conditions are easing or tightening. If the “financing bottleneck” becomes a widely shared concern, it could shift market expectations about when incremental capacity comes online, even if underlying AI demand remains strong.