Practical guidance on securing AI agents, tools, and the systems they act on, written by the team building the trust layer for AI agents.
A consolidated AI governance readiness checklist covering accountability, inventory, policy enforcement, evidence, and incident handling for a systematic review.
AI incident reporting needs specific triggers and escalation paths, since a conventional security incident process often does not clearly capture AI-specific failures.
Auditing AI system activity means sampling actual production behavior against policy, not just confirming logging exists, since existence is not the same as compliance.
Governing third-party AI assistants needs explicit scoping of what access they receive and ongoing monitoring, since vendor trust does not substitute for either.
Internally built agents need the same governance rigor as vendor tools, since being built in-house does not reduce risk and often reduces external scrutiny.
ISO/IEC 42001 provides a dedicated management system structure for AI specifically, useful for organizations whose AI risk has outgrown a bolt-on approach.
ISO 27001's risk-based structure absorbs AI risk naturally, as long as AI-specific threats are actually included in the risk assessment scope, not assumed to be covered.
AI systems fit into existing SOC 2 trust service criteria, but auditors increasingly expect AI-specific evidence within those criteria, not a generic response.
Regulated industries need AI governance mapped explicitly onto their existing regulatory obligations, since a generic AI governance program alone will not satisfy them.
An AI exception process needs a specific owner, a time limit, and a documented reason, or exceptions quietly become the new unreviewed default instead of a controlled deviation.
Human oversight only works if the human reviewing an action has enough specific context to catch a bad one, which most rubber-stamp approval flows fail to provide.
Traceability connects an AI system's output back to the specific model, prompt, data, and policy decision behind it, which matters most exactly when something goes wrong.
