The case of Nvidia and the growing risk of AI and corruption
In 2025, the UN Office of Drugs and Crime and the Organization of American States co-convened a panel (slideshow & video) which examined whether AI is the biggest corruption risk in history.
Key points
- §4815(c), which prohibits BIS from collecting fees for considering or issuing export licenses.” Additionally, last year, Nvidia’s General Counsel, Tim Teter, seemed to interfere in an investigation of Nvidia’s sales to Chinese and Malaysian entities.
- And now we’ve learned that although senior administration officials such as Commerce Secretary Howard Lutnick were warned about the dangers surrounding Nvidia and its now former CEO, they took no action.
- While export controls may be useful and necessary, they are particularly vulnerable to corruption because they sit at the intersection of high-value restricted goods, bureaucratic gatekeeping, in customs, business, and trade policymaking agencies, and complex cross-border supply chains.
I believe that one company, Nvidia, has become the poster child for corruption in the U.S.
Instead, they learned that the corruption of AI did not start inside the technology itself but with its leaders, heads of state, government officials, and tech CEOs, steering the direction of AI governance.
Additional details
- Not surprisingly, both competitors of Nvidia that produce high speed chips such as Google, and, as well as Open AI, Amazon, Anthropic, and Microsoft—three of Nvidia’s biggest clients— support legislation that would further limit Nvidia’s ability to export chips to China.
- As we see today, America’s approach to AI governance, using export controls to regulate the supply of AI and its components, is fueling corruption.
- The now former CEO of Nvidia, Jensen Huang, used flattery and donations to influence the Trump Administration’s AI export policies.
- The panelists feared that AI would enable corruption by making it easier to launder money, give bribes, or produce disinformation.
- In November 2026, the panelists’ deepest fears about the AI-corruption relationship came true, but not in the way they expected.
How this summary was made: extractive summary — built from the sources' own reporting. It is drawn only from the reporting of the sources listed below — read the originals for full detail. How we summarize →
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