Trump will never back a US AI regulator, says departing tech adviser Sriram Krishnan

Reviewed byNidhi Govil

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Sriram Krishnan, Trump's outgoing AI policy advisor, firmly rules out creating an FDA-style AI licensing body, calling it bureaucratic red tape that would stifle innovation. His comments come amid growing AI backlash from voters and $130bn in disrupted data center projects, even as the White House intervened to halt Anthropic's Mythos model on national security grounds.

Trump Administration Rejects Centralized AI Regulation

The Trump administration will not establish a formal US AI regulator despite mounting public concerns and recent government interventions in advanced model releases, according to Sriram Krishnan, the president's departing AI policy advisor. In his first in-depth interview since leaving the White House last month, Krishnan told the Financial Times there will be "never, never" be an "FDA for AI" under President Trump

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. The 42-year-old former venture capitalist, who worked closely with AI tsar David Sacks, emphasized that Trump's stance on AI regulation remains firmly opposed to "burdensome, onerous, bureaucratic red tape" that picks winners and losers

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Source: FT

Source: FT

Light-Touch Oversight Favored Despite National Security Interventions

Krishnan's prediction arrives weeks after unprecedented government action forced Anthropic to withdraw its most capable Mythos model and delayed OpenAI's 5.6 release on national security grounds

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. The Indian-born former Andreessen Horowitz partner argued that setting up a centralized licensing agency requiring "a team of lawyers before you can get a model out" would put "sand in the gears" of the AI revolution and harm American competitiveness against Chinese companies

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. Instead, Krishnan favors industry self-policing through a voluntary framework that gives the government 30 days to review models before release, eventually shifting oversight to an industry-run clearinghouse working with intelligence and defense officials

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. This approach reflects the administration's broader philosophy that stifling innovation through excessive regulation would cede American leadership in artificial intelligence.

Source: Benzinga

Source: Benzinga

Growing AI Backlash Challenges Deregulatory Approach

The administration's light-touch oversight for AI faces significant headwinds from voters and local communities. A large majority of Americans now support stringent regulations to rein in AI, while at least 75 data center projects worth approximately $130bn were disrupted by local opposition in the first three months of 2026, according to researcher Data Center Watch

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. Some in Washington blame the deregulatory zeal for this AI backlash among American voters and within Trump's MAGA coalition, reflecting concerns about data centers and societal impact. However, Krishnan placed responsibility squarely on the industry's "doomer" messaging, arguing that AI leaders "have focused so much on the dystopian narrative and scenarios, whether it is job loss, whether it is [existential] risk" that people question whether they want the technology at all

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Public Equity Stakes Proposed to Address Wealth Concentration

To counter voter sentiment that AI benefits only flow to a few powerful companies, Trump has pushed for companies to donate public equity stakes to the American people, discussing these plans with OpenAI chief executive Sam Altman

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. Despite Silicon Valley warnings about backdoor nationalization, Krishnan supported the initiative, stating "some way for regular people to feel like, OK, when I use this model, or when I see the graphs going up and I watch on CNBC, I am benefiting" would be positive

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. The innovation vs regulation debate intensified after OpenAI's Altman said the government's demand to limit the 5.6 model release was not "optimal," while investors warned against creating an ad hoc licensing regime where frontier models must secure Trump administration clearance

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. Over the past 18 months, Krishnan and Sacks advocated for banning state-level AI safeguards and minimal monitoring of advanced models for national security and cyber security risks, though recent models with powerful capabilities have driven renewed momentum for government control

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