Audit trail

Red Hat launches “asago,” an open-source initiative to automate AI governance from policy to production code. Asago maps policies to risks, assesses them with tailored scenarios, recommends mitigations, and orchestrates deployment, significantly reducing manual effort. It ensures continuous audit trails and infrastructure-agnostic configurations. The project, a collaborative effort with major tech and academic institutions, aims to address the growing need for AI safety and compliance in a scalable manner.

To mitigate risks in AI agentic systems, organizations must prioritize robust identity protocols, auditable logs, policy enforcement, human oversight, rapid revocation, and thorough documentation. Employing tools like SDKs that cryptographically sign actions, similar to blockchain, creates an immutable audit trail. A centralized, verbose system of record for all agentic AI activities is crucial for governance, surpassing scattered text logs. Maintaining an “agentic asset list” with unique identifiers, capabilities, and permissions is essential, aligning with regulations like the EU AI Act’s mandates for ongoing, evidence-based risk management and interpretable AI systems.