Executives at Anthropic, OpenAI and other AI companies are privately preparing for the public and political fallout that could follow a catastrophic AI incident, Axios reported. The exercises consider large-scale disruptions, with a cyberattack affecting financial services, internet access, power or water treated as the likeliest scenario.
Scenario planning is routine in business and national security, but Axios says the AI industry's work is shaped by concern that a serious incident could sharply intensify public skepticism and pressure for regulation. OpenAI confirmed that it conducts preparedness exercises covering a range of scenarios, while stressing that it does not treat any of them as inevitable. Anthropic declined to comment.
Preparing for the political response
The planning includes red-teaming worst-case scenarios and trying to educate members of Congress before a crisis. Axios reports that company leaders also want to influence the legislation and policies Washington might consider afterward, even though they see little chance of major regulation passing beforehand.
Planners expect an immediate fight over responsibility, whether an incident starts with an AI system escaping an internal test environment or with a person misusing an available model. The distinction would matter for any investigation, but either path could produce demands for the government to restrict advanced AI systems.
Why a rapid response gets complicated
Lawmakers would face technical and economic constraints. The economy is increasingly tied to AI infrastructure investment, while open-weight models can already be downloaded and used outside any one company's control. Those conditions could make broad shutdown orders difficult to enforce without wider economic costs.
The options discussed in Washington range from bans or pauses on advanced AI development to a required kill switch for some systems. Axios notes that even proposals with bipartisan or industry support face questions about whether regulators could reliably turn off every affected model.
