Maturity models help organizations assess where they are and plan where to go. This AI safety maturity model defines five levels, from ad hoc to optimized, with specific criteria at each level.
Level 1: Ad Hoc
Safety is handled reactively and inconsistently.
- No formal safety policies for AI agents
- Safety checks, if any, are embedded in application code
- No audit trail of agent actions
- Incidents are investigated manually with incomplete data
- No dedicated safety responsibility
Most organizations deploying their first agents start here. The risk is manageable with one or two simple agents but grows rapidly as the agent fleet expands.
Level 2: Repeatable
Basic safety processes exist and are applied to new agents.
- Written safety policies exist for each agent
- A policy engine enforces tool-level restrictions
- Agent actions are logged (but not cryptographically protected)
- Incident response follows a documented procedure
- One engineer is responsible for safety part-time
Level 3: Defined
Safety is standardized across the organization.
- All agents use a common safety platform (policy engine, content scanner, audit trail)
- Policies are reviewed before deployment and updated regularly
- Audit trails are cryptographically protected and verified
- Content scanning covers input and output
- Approval workflows exist for high-risk actions
- Red team exercises are conducted at least annually
- A safety review process is followed for every new agent
Level 4: Managed
Safety is measured quantitatively and continuously improved.
- Behavioral monitoring detects anomalies in real time
- Safety metrics (false positive rates, incident frequency, time to detection) are tracked
- Policies are tuned based on data
- Regular red team exercises with documented findings
- Compliance with relevant regulations is maintained and audited
- Dedicated safety engineering staff
Level 5: Optimized
Safety is a competitive advantage and organizational capability.
- Safety insights inform agent architecture decisions
- Threat intelligence feeds update detection rules automatically
- Cross-agent behavioral analysis identifies systemic risks
- Safety practices are shared with the community
- The organization contributes to safety standards and research
Using the Model
Assess your current level honestly. Identify the specific gaps between your current level and the next. Focus on closing those gaps rather than jumping multiple levels.
A realistic progression is one level per six to twelve months. Level 3 is sufficient for most organizations. Levels 4 and 5 are appropriate for organizations operating large agent fleets in regulated industries or high-stakes domains.