Intel Corp. Chief Executive Lip-Bu Tan and Hock Tan, his counterpart at Broadcom Inc., have flagged capital access as a potential challenge for the artificial intelligence sector.
The executives shared their observations today during a financial conference in Singapore.
Intel and Broadcom are two of the AI industry’s most important chip suppliers. The former company’s central processing units are in high demand because AI agents need them to run their tools. Last month, Intel disclosed that it has capacity to meet only 50% of orders. Broadcom, in turn, is a major supplier of network processors and custom AI accelerators.
Demand for some data center chips is currently exceeding supply. Hock Tan predicted at today’s financial event that the shortage would ease by 2028 or 2029. Nevertheless, he believes that the imbalance between the demand for computing capacity and the industry’s ability to meet it could persist into 2030.
The executive also addressed several of the other challenges facing the AI sector, including the steep cost of training large language models. He focused on OpenAI Group PBC in particular. Broadcom helped the AI developer design its first custom inference chip earlier this year.
“For now it’s still losing money because they’re spending a lot on training,” Tan said. “So frankly, it doesn’t tell anything at this point except that there is a lot of potential revenue growth out of providing frontier generative AI models.”
Last month, the Financial Times reported that Anthropic PBC’s gross margins exceed 80% when excluding model training costs and revenue shared with go-to-market partners. The company is reportedly on track to generate a positive adjusted operating income for the second quarter in a row.
Hock Tan noted that a sizable portion of AI labs’ enterprise revenue currently comes from pilot projects. “When you are a kid you go to a video arcade, you play,” he said. “Your parents give you $10 of tokens, you finish it in 10 minutes and you haven’t learned anything.”
The executive added that AI labs should acquire more customers who can realize a return on their inference spending. He also commented on the often sharp fluctuations in AI stocks, remarking that many investors “set very extreme expectations only to find out that it’s almost like they are in a casino.”
Despite the investor enthusiasm for AI, Hock Tan flagged that access to capital “might be the biggest constraint” facing the sector. Intel’s Lip-Bu Tan echoed the sentiment, stating that “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.”
Lip-Bu Tan noted that open-source language models from Chinese labs are proving “good enough” for many budget-conscious users. Such models have gained a significant amount of traction over the past year. “I’m a strong believer of open source, that’s the best way to drive efficiency,” the executive said.
The discussion later shifted away from AI. According to Reuters, Lip-Bu Tan predicted that quantum computing could become mainstream within three to five years.
Intel is developing quantum processors that can be made using standard chipmaking equipment. In January, the Argonne National Laboratory deployed a 12-qubit computer developed by the company. Intel disclosed at the time that it hopes to develop quantum systems with hundreds of qubits.