Arm Holdings CEO Rene Haas said it would be extremely difficult for governments to restrict exports of central processing units (CPUs) used in artificial intelligence systems, arguing that CPUs are so widely used across computing that separating “AI chips” from general-purpose processors is not practical.
“CPUs are kind of like oil relative to the application space,” Haas said in an interview, emphasizing that any attempt to block AI-related CPUs would likely require sweeping restrictions across almost all modern computing hardware rather than targeted controls.
Haas noted that unlike graphics processing units (GPUs), which are more directly associated with AI workloads and easier to classify by performance thresholds, CPUs are embedded across nearly every digital system. This makes it difficult to define regulatory boundaries based on memory bandwidth or compute capability without capturing a broad swath of non-AI technology.
The comments come amid ongoing U.S. efforts to limit China’s access to advanced semiconductors used in artificial intelligence development. Washington has already tightened export restrictions on high-end chips and related supercomputing equipment, particularly targeting systems that could accelerate large-scale AI training.
Arm also announced new customers for its AI-focused data center CPU, including ByteDance and Oracle, highlighting growing demand for its architecture in large-scale cloud infrastructure. CEO Haas said demand for the company’s server CPU has strengthened significantly in recent weeks.
The company expects its data center CPU business could generate around $15 billion in annual revenue within five years, marking a major expansion beyond its traditional licensing model. Arm has also doubled its outlook for related chip demand across fiscal years 2027 and 2028, reflecting accelerating adoption in AI-driven workloads.
The broader semiconductor sector continues to benefit from AI-related demand. Intel and AMD have both reported stronger interest in CPUs and hybrid architectures designed to support AI agents—software systems capable of performing tasks autonomously across digital platforms.
As global competition intensifies over AI infrastructure, Arm’s comments underscore a growing challenge for policymakers: regulating AI-specific hardware without disrupting the broader computing ecosystem that underpins modern digital economies.
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