PAM is moving to runtime control for machines and AI agents

At a glance

What this is: This is Delinea’s analysis of the 2026 Frost Radar for PAM, which says privileged access is moving from vault-centric models to real-time control across humans, machines, workloads, and AI agents.

Why it matters: It matters because IAM, PAM, and NHI programmes now have to govern privileged actions at runtime, not just review them after the fact.

By the numbers:

• NHIs outnumber human identities by 25x to 50x in modern enterprises.

👉 Read Delinea's analysis of the 2026 Frost Radar for PAM

Context

Privileged access management is no longer just about storing credentials safely. The control problem now includes machine identities, third-party access, workloads, and AI agents that can take privileged actions faster than traditional review cycles can observe.

That shift changes the governance question for IAM and PAM teams. If privilege is exercised at runtime, then static vaults, periodic certifications, and delayed audit evidence only describe the past while the operational risk is happening in the present.

For teams building NHI programmes, the key issue is not whether automation exists, but whether privileged execution is being governed at the point of use. The practical reference point is the lifecycle and governance model for NHIs, not human-only access administration.

Key questions

Q: Why do static PAM controls struggle with machine-speed privilege?

A: Static PAM controls assume privilege can be reviewed, approved, and audited on a human cadence. That assumption fails when workloads or agents use privilege continuously during automated execution. The result is a control that records access rather than governing it. Teams need runtime enforcement, not only vaulting and periodic review.

Q: When should organisations prioritise JIT access over longer-lived privileged accounts?

A: Organisations should prioritise JIT access when privileged actions are task-specific, repeatable, and carried out by machines or service identities. Long-lived accounts create unnecessary exposure when the access is only needed briefly. JIT is most valuable where the business process can tolerate ephemeral permissions and fast revocation.

Q: What do security teams get wrong about AI agent privilege?

A: Teams often treat AI agent privilege like static service-account access. That misses the fact that agents can choose actions at runtime and combine tools in different sequences. The governance issue is not just credential custody. It is bounding what the agent can do once execution begins, especially across chained actions.

Q: How should PAM, IAM, and NHI teams work together on privileged access?

A: They should share a single view of privileged execution across humans, machines, workloads, and agents. PAM owns control of high-risk actions, IAM governs identity and entitlement structure, and NHI teams cover non-human lifecycle and visibility. The programme works best when those functions align on the same runtime risk model.

Technical breakdown

Why vault-centric PAM breaks at machine speed

Vault-centric PAM assumes privileged access is exceptional, requested, and visible before use. That model works when humans open sessions occasionally, but it breaks when software, pipelines, and agents repeatedly request privilege in the flow of execution. In those cases, the control surface shifts from credential storage to decision timing. The important technical change is that authorization must occur close to execution, with policy evaluated against identity, context, and task scope in real time. Static entitlements and delayed approvals do not constrain actions that are initiated and consumed inside automated workflows.

Practical implication: measure whether privilege decisions can be enforced at session start and during execution, not only during provisioning.

Runtime authorization and zero standing privilege for NHIs

Runtime authorization moves PAM from access administration to action governance. Instead of assuming that a privileged account should remain usable until the next review, zero standing privilege and JIT access make access temporary, task-bound, and context-aware. That matters for NHIs because service accounts, API keys, and workload identities often carry privileges that are broader and longer-lived than the task requires. When a system can request access only when needed, and lose it as soon as the task ends, the attack window narrows materially. The architectural question becomes whether privilege can be issued, observed, and revoked at machine speed.

Practical implication: map privileged NHIs to JIT and ZSP patterns before expanding human review cadences.

What agentic AI changes in privilege governance

Agentic AI creates a different governance problem because the actor can select actions at runtime, not just consume preassigned access. That changes how privilege is interpreted: the same credential can be used in different sequences, against different tools, and in different order depending on the agent’s immediate objective. Traditional PAM controls were designed for known users and known workflows, so they struggle when action paths are dynamic. The challenge is not only credential exposure, but whether the policy engine can bound what an agent is allowed to do once it starts composing actions. In practice, the risk surface is shaped by tool reach, delegation, and execution context.

Practical implication: treat agent permissions as bounded runtime capabilities, not static access grants.

NHI Mgmt Group analysis

Vault-centric privilege management is becoming a control delay, not a control plane. The Frost Radar framing matches what many teams now see in practice: privilege is exercised continuously across machines, workloads, third parties, and emerging agents. Once execution speed exceeds review cadence, the control no longer governs action, it only records it. Practitioners should treat that as a structural governance shift, not a feature gap.

Runtime authorization is the new organising principle for machine identity governance. The important issue is not whether an access request was approved, but whether the identity could act outside the exact conditions intended for that task. That is why PAM, NHI governance, and zero standing privilege now converge around the point of use. Security teams should redesign privilege controls around execution, not entitlement inventory.

Agentic AI makes privilege shape-shift inside the session. Unlike a static workload, an autonomous actor can choose a different sequence of tools and actions at runtime, which means least privilege cannot be fully expressed as a provisioning-time list. That assumption collapses because the actor’s intent is not fixed before execution begins. The implication is that identity governance must rethink how privilege boundaries are defined for dynamic actors.

Continuous discovery is now a prerequisite for credible PAM governance. If organisations cannot see which machine identities and third parties hold privileged access, they cannot evaluate whether runtime controls are covering the real attack surface. The market’s move toward continuous, identity-centric governance validates this shift. Practitioners should expect PAM programmes to be judged on visibility and enforcement together, not separately.

Runtime privilege control is becoming the bridge between human IAM discipline and NHI governance. Human access review processes and machine access controls are converging on the same question: who or what can act, under what conditions, and for how long. That convergence matters because privileged execution no longer cleanly belongs to one identity class. Teams should align PAM, IAM, and NHI operating models before the governance gaps widen.

From our research:

• 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface, according to Ultimate Guide to NHIs.
• Only 5.7% of organisations have full visibility into their service accounts, which means most teams cannot reliably validate where privileged machine access actually exists.
• That is why the NHI Lifecycle Management Guide is the right next resource for teams moving from entitlement inventory to lifecycle control.

What this signals

Runtime governance will become the measurement standard for PAM programmes. The question is no longer whether privileged access exists, but whether teams can constrain it at the point of use across humans, machines, and agents. That favours control models that can evaluate intent, context, and duration in-session rather than after the fact.

With 96% of organisations storing secrets outside secrets managers in vulnerable locations including code, config files, and CI/CD tools, the risk surface remains far broader than most PAM dashboards suggest. Teams should expect more of their control design to shift into pipeline governance, workload identity, and non-human lifecycle management.

Identity blast radius: when one privileged identity can be reused across multiple execution paths, the real governance problem is not access count but action spread. The immediate planning priority is to reduce how far any single machine or agent identity can move once it is active.

For practitioners

• Map privileged identities by execution mode Separate human-admin access from workload, service account, third-party, and AI-agent privilege so each class can be governed with the right timing and review pattern.
• Shift from vault-centric controls to runtime enforcement Prioritise policy decisions at the point of use, where privilege is actually consumed, and verify that automated systems cannot retain standing access between tasks.
• Apply JIT and zero standing privilege to NHIs first Target long-lived service accounts, API keys, and workload identities that still carry persistent elevation, then reduce their usable window to the task duration.
• Review agent permissions as bounded capabilities For AI agents, define what tool use is allowed during a session, then test whether the policy engine can stop chained actions before they expand beyond the original task.

Key takeaways

• PAM is moving from credential storage to runtime privilege control because machine speed has outgrown periodic review models.
• Excessive privilege remains the dominant non-human identity problem, and that risk now extends into automated systems and AI agents.
• Programmes that align PAM, IAM, and NHI governance around point-of-use enforcement will be better positioned for the next phase of identity security.

Key terms

• Privileged Access Management: Privileged Access Management is the set of controls used to govern high-risk access such as admin, root, and delegated operational privileges. In modern environments it must handle human administrators, service accounts, workloads, and AI agents, with tighter controls on when and how privilege can be used.
• Zero Standing Privilege: Zero Standing Privilege is a governance pattern where access is not continuously available and is instead granted only when needed for a specific task. For non-human identities, the model reduces persistent exposure and limits the time a compromised credential can be used.
• Runtime Authorization: Runtime Authorization is the practice of deciding whether an identity may perform an action at the moment the action is attempted. For machine and agentic identities, it shifts control from pre-assigned entitlement to live policy enforcement, which is essential when actions occur at machine speed.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity security are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are responsible for identity security strategy or NHI governance in your organisation, it is worth exploring.

This post draws on content published by Delinea: Built for machine speed, Delinea named a Growth and Innovation Leader on the 2026 Frost Radar for PAM. Read the original.