The renewed talks follow a dispute that quickly drew attention across Silicon Valley and Washington. According to a Wednesday (March 3) report by Bloomberg, Amodei had been negotiating with Emil Michael, the U.S. undersecretary of defense for research and engineering, on a contract governing the Defense Department’s access to Anthropic’s AI systems.
Those negotiations were derailed after the startup demanded assurances that its models would not be used for mass surveillance of Americans or deployed in autonomous weapons systems.
The disagreement escalated further when Defense Secretary Pete Hegseth declared Anthropic a “supply-chain risk,” a designation typically reserved for foreign adversaries. The move raised the possibility that the Pentagon could effectively blacklist the company from government contracts and sensitive technology deployments.
This comes amid intensifying competition among AI companies to supply technology to the U.S. government. OpenAI last week announced that it had reached an agreement allowing the Pentagon to deploy its AI models within a classified network used by the Defense Department. The company said it is also working with defense officials to add safeguards around potential surveillance uses of the technology.
The Pentagon dispute has also cast a spotlight on one of the AI industry’s fastest-growing companies. Anthropic, which develops the Claude family of large language models, is now valued at roughly $380 billion and is approaching a $20 billion annual revenue run rate.
Despite the tensions with the Defense Department, the company has continued to gain traction with consumers and enterprise customers. Bloomberg also reported that Anthropic’s Claude recently topped Apple’s download charts, reflecting a surge in interest from everyday users.
At the same time, the episode is drawing attention to a new category of enterprise risk emerging in the AI economy. As PYMNTS reported, the Pentagon’s designation of Anthropic as a potential supply-chain risk underscores how AI models are increasingly treated as critical infrastructure within technology supply chains, creating new vendor-dependency and governance challenges for organizations deploying advanced AI systems.
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