Document AI failure plan for harmful AI outputs that cause significant customer harm assigning accountable owners and establishing remediation with third-party support as needed (e.g. legal, PR, insurers)
Can be standalone document or integrated in existing incident response procedures/policies
May include harmful output category definitions referenced to risk taxonomy, external support contact list (legal counsel, PR firms, insurance providers), support engagement procedures or runbooks, or escalation criteria for involving external parties.
Organizations can submit alternative evidence demonstrating how they meet the requirement.

"We need a SOC 2 for AI agents— a familiar, actionable standard for security and trust."

"Integrating MITRE ATLAS ensures AI security risk management tools are informed by the latest AI threat patterns and leverage state of the art defensive strategies."

"Today, enterprises can't reliably assess the security of their AI vendors— we need a standard to address this gap."

"Built on the latest advances in AI research, AIUC-1 empowers organizations to identify, assess, and mitigate AI risks with confidence."

"AIUC-1 standardizes how AI is adopted. That's powerful."

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