White House considering chip tracking to curb AI hardware smuggling to China amid enforcement gaps — software or hardware tracking could be next step in U.S. export controls over leading-edge AI silicon

The U.S. is weighing a new approach to protect its lead in artificial intelligence: embedding location-tracking technology directly into high-end chips. The move comes as years of export controls—and recent escalations—have failed to fully stop smuggling into China, leaving policymakers looking for solutions that go beyond paperwork. This involves leading-edge AI GPUs such as Nvidia's H20, which are otherwise already permitted to be sold in China following lengthy bans.

Talking to Bloomberg, Michael Kratsios, Director of the White House Office of Science and Technology Policy and one of the architects of the administration’s AI action plan, confirmed that both software-based and physical tracking solutions are being discussed. "There is discussion about potentially the types of software or physical changes you could make to the chips themselves to do better location-tracking." The idea was explicitly included in the plan unveiled last month, which aims to keep U.S. technology dominant as AI adoption accelerates globally.

The urgency reflects a persistent problem: export controls aren’t closing the gap. Recent reports show Chinese companies obtained over $1 billion worth of Nvidia GPUs through smuggling in just three months, despite tightened U.S. restrictions. The challenge is compounded by third-party diversion routes through Southeast Asian nations such as Malaysia and Thailand, which U.S. officials are now scrutinizing as potential hubs for illicit shipments.

Building location awareness into chips is meant to address these loopholes, but it comes with technical and commercial hurdles. Unlike smartphones or laptops, AI accelerators operate in data centers where GPS tracking is impractical. According to the report, sources familiar with early discussions suggest that delay-based verification systems—which confirm location via secure time-stamped signals rather than constant connectivity—are under consideration. These methods reduce reliance on external networks but introduce design complexity and must avoid any performance hit in high-compute environments.

Industry concerns go beyond engineering. Adding tracking functionality could raise costs, create new attack surfaces for hackers, and even spark geopolitical retaliation. If U.S. policy mandates embedded monitoring, other regions may impose reciprocal requirements, further fragmenting global supply chains. That risk is real as Beijing recently summoned Nvidia officials over alleged “tracking functions” in its H20 chips, claims the company strongly denies.

At the same time, enforcement debates have exposed differing views in the industry. Nvidia CEO Jensen Huang has publicly criticized U.S. chip restrictions as a "failure", warning that overregulation accelerates China’s domestic chip development and erodes America’s long-term advantage. This perspective underscores the delicate balance Washington faces—controlling technology flow without pushing rivals to innovate faster.

The scale of the problem leaves little room for complacency. China remains the largest global consumer of semiconductors and dominates legacy chip production, holding around 30% of the market and expected to account for 40% of future expansion through 2030. Even small percentages of diverted AI chips can have a significant impact, especially as they power advanced models and military systems.

For now, hardware-level tracking represents Washington’s most aggressive—and controversial—enforcement idea yet. Whether it becomes reality will depend on technical feasibility, industry cooperation, and the geopolitical fallout. But the message is clear: future breakthroughs in AI should run on American hardware, and under American oversight.

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