6.7 Continuous review cadence
The monthly, weekly, and quarterly rhythm that keeps AI security controls from drifting as tools and capabilities evolve.
Last reviewed: August 18, 2026
Continuous review cadence: what security teams need to know
AI security is not a one-time rollout task. New models, connectors, agent modes, browser features, data controls, and audit endpoints can change the risk of an approved workflow — and vendors also retire surfaces, which can invalidate policies and pilots built on them.
Cadence gives teams a rhythm: weekly alerts, monthly analytics, quarterly access and red-team reviews, and immediate review after incidents or major releases.
Common continuous review cadence security failures
Controls are reviewed only during annual audit.
Vendor releases add features that bypass old policy assumptions.
Exceptions never expire.
Usage shifts to a new surface without owner review.
Red-team findings are not retested.
Continuous review cadence security controls checklist
Review SIEM alerts weekly for high-risk surfaces.
Review usage, spend, and adoption monthly.
Review high-risk roles, connectors, MCP servers, plugins, and exceptions quarterly.
Retest red-team findings after fixes.
Trigger review after incidents, vendor releases, deprecation announcements, new data classes, and new write actions.
Anthropic
Overview
Anthropic continuous review should revisit custom roles, connector permissions, Claude Code managed settings, MCP allowlists, plugin, skill and hook inventories, Managed Agent definitions, scheduled deployments, Cowork execution modes, Office add-ins, data retention, and monitoring coverage. Unattended automation deserves its own review line. Cowork scheduled tasks run remotely by default, but tasks that need local folders or desktop applications run locally and require the desktop to remain available. Team and Enterprise admins control scheduled tasks through the Cowork admin toggle.
Re-review when a new Claude surface, connector, or automation path enters production. Cowork now spans web, desktop, and mobile, with remote sessions that follow the user across devices and local capabilities that still depend on desktop. Review telemetry whenever that boundary changes. Cowork and Claude's Office agents currently sit outside the Compliance API and data exports, so any logging change should trigger an evidence-map review.
Add Claude Tag to the cadence: review connected Slack workspaces, member restrictions, allowed channels and DMs, service accounts, Access-bundle inheritance, domains, repositories, saved memory, spend limits, routines, and optional network-event exports. Re-run the review when a channel changes audience or classification, because the same shared credentials become available to every member in scope.
Anthropic documentation
Applicable Harmonic guides for Anthropic
OpenAI
Overview
OpenAI's July 2026 release changed the control map at once. ChatGPT Desktop (Work / Codex) combines Chat, Work, and Codex, and existing Codex desktop installations update into it. The App Directory became the Plugin Directory, and plugins can package skills, apps, and app templates. ChatGPT Atlas is scheduled to retire on August 9, 2026. Each change warrants a policy, deployment, support, and evidence review.
Recurring review should cover ChatGPT RBAC and action controls, Work web and mobile permissions, local Codex clients and managed desktop configuration, plugins and connected apps, Sites publishing, Computer Use, governance exports, and scheduled tasks. OpenAI documents web and mobile Work as a cloud surface and desktop Work as a local-capable surface. Review both control planes, and re-review when users move among Chat, Work, Codex, the API Platform, and external applications.
OpenAI documentation
Applicable Harmonic guides for OpenAI
Frequently asked questions about continuous review cadence
How often should AI controls be reviewed?
Use weekly alert review, monthly usage review, quarterly access and extension review, and event-driven review after incidents or major vendor changes. The event-driven trigger matters most in practice, because vendor deprecations and renames arrive on the vendor's calendar, not yours.
What should be reviewed monthly?
Review usage, spend, new surfaces, adoption shifts, and policy exceptions. Monthly review is where surface drift shows up first — usage moving from chat to coding agents, API keys, or scheduled automations — while the shift is still small enough to govern.
What should be reviewed quarterly?
Review roles, connectors, MCP servers, plugins, skills, red-team results, and high-risk workflows. Include unattended automation inventories such as scheduled agent deployments, Cowork scheduled tasks, and ChatGPT scheduled tasks. Check whether each runs remotely or needs a local desktop, and whether its owner and permissions are still valid.
What triggers an out-of-cycle review?
Incidents, vendor releases, deprecation announcements, new data classes, new write actions, new connectors, and audit gaps. The July 2026 ChatGPT desktop consolidation changed installation, local access, plugin packaging, and product naming together. Atlas retirement on August 9, 2026 adds a dated migration trigger. Anthropic's expansion of Cowork across web, desktop, and mobile similarly changes where work runs and where evidence lives.
Who owns the cadence?
Security should own the rhythm: the calendar, the trigger list, and the escalation path when a review finds drift. Platform, identity, compliance, and business owners own their control evidence, because they are the ones who can actually re-verify a role grant or a connector scope.
Applicable regulations and frameworks
G.1 Map your controls to NIST AI RMF and CSF 2.0
This article supplies implementation evidence for the NIST AI RMF and matching NIST CSF 2.0 outcomes.
G.2 EU AI Act obligations for deployers
Conditional: for an in-scope high-risk system, this supports ongoing monitoring and reassessment after material change.
G.3 DORA and AI resilience in financial services
Conditional: for a DORA-regulated workflow, this supports monitoring, investigation, audit evidence, and incident reporting.
G.5 SANS Critical AI Security Guidelines mapping
This article implements relevant SANS Monitoring and GRC guidance.
G.6 Write an AI Acceptable Use Policy that holds up
This article supplies a technical or process control used to enforce the acceptable-use policy.
G.7 Ownership and RACI for AI security
This control depends on the ownership and evidence responsibilities defined in the RACI.
G.8 ISO/IEC 42001 AI management system
This article supports ISO/IEC 42001 AIMS preparation through periodic review, corrective action, and continual improvement.
G.9 HIPAA controls for AI systems handling PHI
Conditional: for a workflow handling ePHI, this supports HIPAA audit controls, activity review, and investigation evidence.
G.2, G.3, G.4, and G.9 are conditional mappings. They apply only when the deployment is within the legal or regulatory scope described on the linked governance page.
Related handbook guidance
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