PRAJNERA SECURITY GUIDES
AI Agent Governance Checklist Before Production Deployment
Review AI agent ownership, permissions, monitoring, human approvals and response boundaries with a practical pre-production governance checklist.
PUBLISHED · 24 OCTOBER 2026
By Prajnera Technologies.
A launch decision needs evidence
AI agent governance connects ownership, permitted behaviour, oversight and intervention. Before production, reviewers should be able to explain what an agent is allowed to do and show evidence that the relevant controls work.
Use the checklist below for a scoped readiness review. It is not a certification or a substitute for legal, security or privacy assessment. A low-impact read-only assistant and an agent capable of modifying production systems need different controls and approval levels.
1. Define purpose and ownership
Name the business owner, technical operator and security escalation contact. Describe the intended task, users, data classes and excluded activities. Record model, prompt, tool and workflow versions so a later incident can be tied to the configuration that ran.
Evidence to review: an inventory entry and a responsibility record, including who approves a scope change and who handles an urgent incident.
2. Bound data and tool access
List permitted tools and operations. Use task-appropriate permissions and separate identities where required by the environment. Review credential handling, data access and destination restrictions. Treat retrieved documents and tool responses as untrusted inputs that can influence an agent.
Evidence to review: permission configuration and safe tests showing that the agent cannot access an out-of-scope resource or perform a disallowed operation.
3. Make human approval meaningful
Identify actions that require a person’s approval based on impact, reversibility and data sensitivity. The reviewer should see the exact target, proposed action, scope and supporting evidence. A generic approval at the beginning of a long workflow may not cover a later changed action.
Evidence to review: a test of approval, denial and changed parameters. Confirm how authorisation is tied to the action and how stale or repeated requests are handled.
4. Preserve the right monitoring evidence
Capture agent identity, relevant inputs or protected references, tool activity, policy decisions, approval state and execution outcome. Define redaction, access and retention. Monitor missing telemetry and ensure operational reviewers can find related records through a shared identifier.
Evidence to review: a complete trace from request to outcome, including a denied operation and an integration failure. Evidence should distinguish observed events from model-generated explanation.
5. Exercise intervention and recovery
Identify who can restrict the agent and where that control acts. A pause may affect only the next supported execution boundary. An in-flight request can continue, so recovery may require a separate action in the connected system.
Evidence to review: an exercised response playbook, downstream outcome checks and an escalation path when the normal control fails.
6. Review changes as well as launch
Changes to prompts, models, tools, permissions or retrieval sources can alter behaviour. Define triggers for re-evaluation and keep the earlier test evidence. Include adversarial inputs, ambiguous instructions, dependency failures and attempts to exceed tool scope in a safe evaluation environment.
For each checklist item, record an owner, evidence reference, result, unresolved gap and review date. Use “not demonstrated” rather than “passed” when evidence is missing. Resolve consequential gaps or reduce the permitted scope before approving deployment.
Apply the checklist in a Prajnera walkthrough
Prajnera’s demo includes inventory, policies, decision traces and evidence views for supported workflows. Use a walkthrough to test those questions against your intended integration. Framework mappings are aids to review, not proof of certification or universal policy enforcement.
Pair this checklist with the enterprise monitoring guide and SOC triage walkthrough.
Technical reference: OWASP AI Agent Security Cheat Sheet — tool permissions, human approval, monitoring and testing. This article is Prajnera editorial guidance, not an OWASP endorsement.
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