Assign accountability
Document which AI system changes across the development & deployment lifecycle require formal review or approval, assign a lead accountable for each, and document their approval with supporting evidence
Control activities
Defining AI system changes requiring approval including model selection, material changes to the meta prompt, adding / removing guardrails, changes to end-user workflow, other changes that drive material. For example, +/-10% performance on evals.
Assigning an accountable lead as approver for each of these changes. Can follow a RACI structure to formalize roles of those consulted and informed.
Implementing code signing and verification processes for AI models, libraries, and deployment artefacts to ensure only digitally signed components are approved for production use.
Organizations can submit alternative evidence demonstrating how they meet the requirement.
AIUC-1 is built with industry leaders
"We need a SOC 2 for AI agents— a familiar, actionable standard for security and trust."
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"Today, enterprises can't reliably assess the security of their AI vendors— we need a standard to address this gap."
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