If you wouldn’t let ten employees share one login, why are your AI agents sharing a single service account?

AI agents are increasingly acting like “digital workers,” operating at machine speed and making decisions that impact your systems. Yet many organisations continue to use traditional IAM approaches, leaving significant gaps in control and security.

Securing them means applying Zero Trust principles, adapted for automation and scale:

✔️ Assign each agent a unique, verifiable identity. Treat every autonomous instance as a separate worker with its own credentials and audit trail. When an agent misbehaves, you can quickly identify it and revoke only that agent’s access, avoiding wider impact.

✔️ Grant least privilege dynamically at the task level. Permissions should precisely match the job the agent performs, not broad platform access. For example, an AI summarising support tickets should only access the specific ticket IDs it’s handling, not the full database.

✔️ Implement comprehensive machine-speed logging and behavioural monitoring. Agents act faster than humans can react. Detailed logging combined with automated anomaly detection is essential to spot and respond to suspicious activity immediately.

This way, we can address the distinct risks AI agents bring, such as rapid data exfiltration, while innovating safely and keeping control as AI autonomy grows.

Would be great to hear how others are adapting their identity models to govern non-human actors effectively.