The chief executives of Intel and Broadcom stated Monday that access to capital is emerging as a potential primary constraint on the expansion of the artificial intelligence sector. The remarks were made by Broadcom CEO Hock Tan and Intel CEO Lip-Bu Tan during the DBS Asia Future Forward Conference in Singapore.
Hock Tan identified financing as a more significant obstacle to AI development than other widely discussed issues such as the availability of semiconductors, memory chips, or electricity.
“[What] I think might be the biggest constraint is capital,” Hock Tan said at the event. He explained that while the industry has addressed a series of supply bottlenecks over the past two years, securing the necessary funding for large-scale infrastructure remains a critical challenge.
Lip-Bu Tan of Intel concurred, highlighting the rising cost of capital and the long-term necessity for companies to prove their AI investments are profitable.
“If there’s any challenge in the front, it’s capital and the cost of capital, and then the other part is in the longer run, people want to see the ROI [return on investment],” he said.
The comments come as technology companies make substantial investments in data centers, advanced chips, and power infrastructure to meet the demand for AI computing capacity. According to the executives, rising borrowing costs could make it more expensive to finance these long-term projects.
Despite concerns over capital, both CEOs indicated that near-term demand for AI infrastructure remains strong.
“There is more demand for compute infrastructure than we can supply,” Hock Tan stated, adding that this imbalance between supply and demand could extend through 2029.
He also noted that other supply issues are expected to lessen over time. “[In the] last two years we have seen a series of bottlenecks that keep coming out, but then we overcome it,” Hock Tan said. “Memory shortage today might not be that way a year from now.”
Looking forward, the executives said that sustained growth in the AI sector will depend on widespread business adoption and the technology’s ability to deliver measurable economic benefits. Hock Tan stated that demand could moderate if the capabilities of AI models do not continue to advance or if business adoption rates are lower than anticipated.
Lip-Bu Tan added that companies will face increasing pressure to demonstrate tangible returns from their AI expenditures, such as improved efficiency or the creation of new business models.
