COMPEL Glossary / agent-lifecycle-management
Agent Lifecycle Management
Agent lifecycle management is the end-to-end governance process covering the creation, registration, testing, deployment, monitoring, updating, and eventual retirement of AI agents within an enterprise.
What this means in practice
Each stage has specific governance requirements: registration ensures the agent is cataloged and its capabilities documented, testing verifies it behaves within defined boundaries, deployment requires authorization, monitoring tracks ongoing performance and compliance, and retirement ensures clean decommissioning without orphaned processes. For organizations deploying agentic AI at scale, lifecycle management prevents the accumulation of ungoverned agents that could take unauthorized actions or consume resources without accountability. This discipline is covered in COMPEL Module 3.4, Article 11, where it is positioned as a core component of enterprise agentic AI governance architecture.
Why it matters
Without systematic lifecycle management, organizations accumulate ungoverned AI agents that take unauthorized actions, consume untracked resources, and operate without accountability. As agentic AI scales across the enterprise, the risk of orphaned or rogue agents increases exponentially. Lifecycle management provides the governance discipline that prevents agent proliferation from becoming an unmanaged operational and security risk.
How COMPEL uses it
Agent lifecycle management is a core component of enterprise agentic AI governance, covered in the Model stage where the lifecycle governance process is designed. The Produce stage operationalizes registration, testing, deployment authorization, and monitoring. During Evaluate, lifecycle compliance is audited and agents are reviewed for continued authorization. The Governance pillar ensures every agent is cataloged with documented capabilities, permissions, and ownership.
Related Terms
Other glossary terms mentioned in this entry's definition and context.