A comparison of the two security models most teams end up choosing between when agents start touching production systems.
Most teams do not choose shared service accounts because they believe it is the right long-term control model. They choose it because it is the fastest path to getting an agent into production. The problem is that the same shortcut breaks attribution, incident response, and least-privilege controls the moment the agent does anything important.
With a shared service account, the agent inherits whatever the account can do, and every downstream action looks identical to every other workflow using that account. This reduces provisioning work but makes the audit trail ambiguous. If an agent writes to the wrong resource or reads something it should not have, the evidence often points to a shared process identity instead of the actual actor.
Per-agent identity means the subject in the log matches the actual agent or workflow that acted. That is what makes least privilege, surgical revocation, and reviewable audit evidence possible. The tradeoff is that teams need a provisioning and rotation model instead of relying on a single static credential.
The transition does not have to be a platform rewrite. Teams can keep the same agent runtime and move the credentialing layer first: issue a stable subject for the workflow, capture its protected actions, and then narrow the authorization scope over time. That approach gives you evidence quickly while still improving the control plane.
If you are comparing these models in a buying cycle, the relevant product surface is not a generic IAM promise. It is whether the platform can actually support per-agent identity and policy-aware logging in a production workflow.
If your team is moving off shared accounts, compare the control model with the feature surface for per-agent identity and the integration path needed to deploy it.
Autonomous agents can read files, call APIs, and modify databases - all without a human in the loop. Without a stable, verifiable identity attached to each agent, your audit trail is fiction and your blast radius is unlimited.
A practical rollout guide for teams that need attributable logs, policy context, and exportable evidence for production AI agents.
