Agent identity in the age of AI
The adoption of AI agents in enterprise contexts raises a critical question: who is interacting with which system, and how is identity being managed when agents act autonomously? A security-first approach to AI agent identity involves robust authentication, continuous risk scoring, and auditable decision traces that enable operators to understand agent behavior. As agents gain access to sensitive data and critical workflows, organizations need to implement layered safeguards, including least-privilege policies, token-based authorization, and comprehensive monitoring to prevent credential misuse or unintended escalations. This piece argues that agent identity is not a single feature, but a governance paradigm that must be embedded into every stage of the AI lifecycle—from development and testing to deployment and operation.