No Access Review
Agent permissions are not periodically reviewed.
12 patterns for this goal
Agents operate without accountability, transparency, or compliance controls — there’s no audit trail of actions, no human owner responsible for failures, no rollback plan when things go wrong, no incident process, and no mechanism to prove to regulators that decisions were made according to policy. Governance failures are peculiar because the agent may make correct decisions, but the governance structure around the agent is absent — regulators and auditors can’t verify compliance even though the agent behaved correctly, because the compliance infrastructure doesn’t exist.
Across all 12 patterns, the single most reliable mitigation is mandatory governance infrastructure: (1) assign a human owner to every agent (non-delegable accountability); (2) audit every action with decision rationale (prove what happened and why); (3) map every business policy to technical controls (policies aren’t just documents, they’re enforced); (4) tier decisions by risk (high-stakes decisions get mandatory review); (5) define incident response procedures (if something fails, there’s a process). Cases where governance is built into the system consistently survive audits and can demonstrate compliance. Cases where governance is left to documentation or verbal agreements consistently have gaps when tested.
Governance covers the infrastructure for accountability (human owner, incident process, audit log, rollback). Approval workflows cover the decision gates (who decides what). Both are governance, but governance is the system-level accountability structure, approval is a specific decision mechanism.
Documentation is necessary but not sufficient. Without enforcement, governance is aspirational. The reliable approach is to build governance mechanisms into the system: audit logging as a mandatory dispatch-layer wrapper (not optional per-tool), rollback as an automated process (not manual ad-hoc), change management as a gated deployment (not post-deployment documentation).
Assign ownership by decision category or risk tier. Example: one owner for routine decisions, escalation to higher owner for high-stakes decisions. The point is that every decision can be traced to a named owner; if something goes wrong, you know who was responsible and can involve them in root-cause analysis.
No-audit-log (no record of decisions) and no-human-owner (no accountability) are highest-priority because they violate fundamental governance principles and expose the organization to regulatory risk. No-incident-process is next because it prevents learning from failures.
| Pattern | Mechanism |
|---|---|
| No Access Review | No mechanism to review who accessed what data or when; access patterns invisible |
| No Approval Boundary | No clear definition of what decisions require approval; all decisions treated identically |
| No Audit Log | No record of actions taken or decisions made; compliance audits cannot reconstruct decision history |
| No Change Management | Agent changes ship without approval or rollback plan; failures can’t be rolled back |
| No Data Retention Control | Data is not deleted when retention period expires; regulatory violation |
| No Human Owner | No one is accountable for agent decisions; incident root-cause analysis impossible |
| No Incident Process | No defined response process when failures occur; learning from incidents impossible |
| No Policy Mapping | Business policies defined in documentation but not mapped to technical controls; gaps between policy and enforcement |
| No Risk Tiering | All decisions treated identically regardless of risk/impact; high-stakes decisions not tagged for extra review |
| No Rollback Process | No way to undo bad decisions; false positives or incorrect decisions are permanent |
| No User Notification Rule | Users affected by agent decisions not notified; transparency and fairness violated |
| No Vendor Risk Control | Third-party vendors integrated without risk assessment or controls; supply-chain risk ignored |
Total: 12 patterns
Agent permissions are not periodically reviewed.
Unclear which actions require human approval.
Cannot reconstruct what the agent saw, decided, and did.
Prompt/tool/model changes go live without review.
Agent stores sensitive data unnecessarily.
No accountable owner for agent decisions/actions.
No defined response for agent-caused failures.
Agent behavior not mapped to company/regulatory policies.
Low-risk and high-risk actions treated the same.
Cannot revert bad prompt/model/tool changes quickly.
Users are not told AI is acting or making decisions where needed.
External model/tool vendors create unmanaged risk.