How should teams govern vendor and AI access to clinical systems?

Why This Matters for Security Teams

Vendor accounts and AI-driven service accounts are often given more access than human users because they are created to get work done quickly. In clinical systems, that shortcut becomes risky fast: these identities can touch EHR workflows, imaging platforms, scheduling, billing, and data exchange. NHI Management Group’s Ultimate Guide to NHIs frames this as a lifecycle problem, not a one-time provisioning task.

The core issue is not just least privilege, but whether access can be tied to a specific task, session, and owner. If a vendor or AI agent has standing access, the organisation inherits a standing blast radius. Security teams also have to account for secrets exposure, because a compromised token can outlive the relationship that created it. The OWASP Non-Human Identity Top 10 highlights this risk pattern directly: credentials, not just software flaws, become the path into production systems. In practice, many security teams discover this only after a vendor credential or automation token has already been reused outside its intended clinical task.

How It Works in Practice

Effective governance starts by treating vendor and AI access as temporary, named, and auditable. That means every non-human identity should map to a business owner, a technical owner, and a defined clinical purpose. Access should be issued just in time, scoped to a task, and revoked automatically when the task ends. For AI agents, that usually means runtime policy checks rather than static role assignment, because the agent may chain tools, call APIs in sequence, or change behaviour based on the data it sees.

A workable pattern in healthcare usually includes:

• Named sponsorship for every vendor account, integration, or AI workload.
• Ephemeral credentials with short TTLs instead of long-lived static secrets.
• Session recording and request logging for all privileged clinical actions.
• Pre-approved use cases, with policy-as-code enforcing what the identity may do at runtime.
• Automatic revocation and break-glass review when a vendor engagement ends or an AI workflow changes.

This is where workload identity matters. For autonomous systems, the identity primitive should be cryptographic proof of what the workload is, not only the secret it presents. Standards work around agentic controls is still evolving, but current guidance from the NIST Cybersecurity Framework 2.0 supports continuous control, while NHI lifecycle guidance from Lifecycle Processes for Managing NHIs reinforces ownership, onboarding, rotation, and retirement. Where clinical systems support it, those workflows should be paired with runtime controls that reflect the actual task, not the vendor relationship. These controls tend to break down in legacy EHR integrations that cannot enforce per-session policy or automatically revoke access without manual intervention.

Common Variations and Edge Cases

Tighter access controls often increase operational overhead, requiring organisations to balance patient-safety continuity against administrative friction. That tradeoff becomes visible in emergency support, clinical device maintenance, and after-hours vendor troubleshooting, where teams may need controlled exceptions.

Best practice is evolving, but current guidance suggests using a narrow break-glass path with explicit approval, short expiry, and complete audit capture. For AI assistants and automation pipelines, the same rule applies: if the system can initiate actions on its own, it should not inherit broad standing privileges just because it belongs to a trusted vendor. The Top 10 NHI Issues research is useful here because it shows how credential sprawl, weak rotation, and poor lifecycle control create avoidable exposure. Teams should also be cautious with shared vendor accounts, because shared access makes attribution and revocation difficult, especially when multiple integrations operate against the same clinical environment. Where the vendor only supports static accounts, the safest interim approach is to place a compensating control layer in front of the clinical system rather than accept permanent exception access.

Related resources from NHI Mgmt Group

• How should security teams govern API keys used for generative AI access?
• How should healthcare teams govern AI agents that access clinical systems?
• How should teams govern tokenized AI API access when usage rights can be traded?
• How should security teams govern non-human identities that have persistent access?