PAM market consolidation is shifting toward AI-era privilege control

At a glance

What this is: Delinea’s Frost Radar placement is a signal that PAM is being evaluated through AI-era privilege control, runtime governance, and platform integration depth.

Why it matters: For IAM practitioners, this matters because privilege controls now have to span human users, service accounts, and AI agents without fragmenting governance across separate tools and workflows.

By the numbers:

• The Frost Radar analyzed the top 11 PAM vendors globally based on market share and worldwide business presence.
• In 2025, Delinea’s estimated year-over-year growth outpaced the overall PAM market growth rate of 19.7%.
• Delinea’s platform includes over 600 prebuilt integrations across more than 145 vendors.

👉 Read Delinea's analysis of its Frost Radar PAM 2026 recognition

Context

Privileged access management is no longer just about vaulting credentials and monitoring admin sessions. In AI-era environments, PAM has to govern access across human users, service accounts, machine identities, and agentic systems that may change how and when they use privilege at runtime.

Delinea’s Frost Radar recognition matters because it reflects where the market is moving: toward consolidated control planes that combine just-in-time access, session oversight, identity analytics, and integrations with adjacent identity and security stacks. That direction raises the bar for every IAM programme that still treats PAM as a narrow administrative control rather than a broader privilege governance layer.

The practical question for security leaders is whether their current model can enforce Zero Standing Privilege, continuous discovery, and runtime authorisation without creating a new patchwork of disconnected controls. The answer will shape how well identity governance holds up as machine and AI identities continue to expand.

Key questions

Q: How should organisations govern privileged access for AI agents and machine identities?

A: Treat AI agents and machine identities as governed privilege holders, not background systems. The key is to bind access to task scope, runtime context, and revocation logic rather than to a long-lived account. If access cannot be proven temporary and attributable, it is not well governed. Use one control model across humans, service accounts, and agentic actors where the privilege risk is similar.

Q: Why do standing privileges create more risk in hybrid environments?

A: Standing privileges persist across sessions, platforms, and operational handoffs, which expands the window for misuse. In hybrid estates, that persistence often survives automation boundaries and cloud transitions, so the same entitlement can be abused in more than one environment. The governance problem is not only exposure, but duration and reuse.

Q: How do security teams know whether Zero Standing Privilege is working?

A: Look for evidence that elevation is issued only when needed, expires automatically, and cannot be reused outside the approved task. If users, service accounts, or automation retain the same privilege between jobs, ZSP is only partial. Governance success means access disappears when the task ends, not when someone remembers to remove it.

Q: What should IAM teams change when PAM expands beyond admin access?

A: They should connect PAM policy to identity lifecycle, telemetry, and entitlement review so privilege is governed continuously rather than only at approval time. That requires shared ownership across IAM, IGA, and security operations. The practical goal is to understand where privilege lives, how it is used, and what removes it.

Technical breakdown

Why PAM is becoming a control plane for human, machine, and AI identities

Traditional PAM focused on vaulted credentials, session recording, and elevated access approvals. The current model is broader: the control plane must also handle continuous discovery, JIT or JEP provisioning, policy-based authorization, and analytics that treat service accounts and AI agents as governed identities rather than background infrastructure. That matters because privilege is now distributed across workloads, integrations, and delegated tooling, not just administrator logins. When access decisions move closer to execution time, static entitlement models lose precision. Practical implication: teams should evaluate whether PAM is operating as an identity control layer or only as an admin-access tool.

Practical implication: inventory where privileged decisions are made at runtime and confirm PAM policies reach those decision points.

What AI-driven privilege analytics change for identity governance

AI-driven auditing in PAM is not simply about better dashboards. Its value is in correlating session behaviour, identity context, and anomaly signals fast enough to catch privilege misuse while access is active. For environments with service accounts and AI agents, this matters because the risk is often not initial authentication but unexpected privilege use once access is granted. Analytics that can distinguish normal automation from abnormal escalation help reduce false confidence in “approved” access paths. Practical implication: organisations need to validate whether their telemetry can distinguish routine machine activity from privilege abuse in real time.

Practical implication: test whether your monitoring can distinguish normal automation from privilege misuse in the same session.

Zero Standing Privilege is the real benchmark, not credential storage

Zero Standing Privilege changes the test from “are secrets stored safely?” to “does anything retain access when it is not actively needed?” That shift is important across hybrid and multicloud environments where credentials can persist in scripts, workflows, or orchestration layers even when a vault exists. A PAM programme that only centralises secrets but leaves long-lived privilege in place has reduced sprawl, not standing access. Practical implication: measure whether access is truly ephemeral, not just centrally managed.

Practical implication: audit which privileged pathways still persist between tasks, sessions, and deployments.

Threat narrative

Attacker objective: The attacker aims to turn privileged access into durable control over systems, data, or identity infrastructure.

1. Entry occurs when attackers obtain privileged credentials, session access, or delegated access paths that were meant to be temporary but remain usable beyond their intended scope.
2. Escalation follows when standing privilege, overbroad roles, or weak runtime controls let the attacker move from a single account to broader administrative access across connected systems.
3. Impact is the abuse of privileged access to alter configurations, exfiltrate sensitive data, or persist inside core identity and infrastructure layers with minimal resistance.

Breaches seen in the wild

• Moltbook AI agent keys breach — Moltbook breach exposed 1.5M AI agent keys.
• MongoBleed breach — MongoBleed exposed secrets across 87K MongoDB servers.

Read our 52 NHI Breaches Analysis report for a comprehensive view of breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

PAM is being evaluated as runtime identity governance, not just privileged credential storage. The Frost Radar emphasis on AI-driven controls, JIT access, and integration depth reflects a market that now expects PAM to govern access at the moment of use. That shift matters because the old definition of PAM assumed privilege was a static condition. Practitioners should read this as a move from vault management to continuous privilege control.

Zero Standing Privilege is becoming the more defensible baseline for hybrid identity programmes. When access spans SaaS, multicloud, on-premises, and air-gapped environments, persistent elevation creates more governance risk than the organisation can comfortably absorb. The discipline now is not whether privilege exists, but whether it can be proven ephemeral. Security teams should treat standing access as a structural liability, not an optimisation choice.

AI-era privilege control exposes the limit of tool-siloed governance. The article’s emphasis on integrations and bidirectional identity risk signals shows that privileged access decisions increasingly depend on context from IAM, IGA, SIEM, SOAR, and cloud controls. No single console can solve that coordination problem on its own. Practitioners should expect PAM roadmaps to be judged by how well they connect, not just how much they consolidate.

Identity governance is shifting toward continuous discovery of machine and agentic privilege paths. The inclusion of AI agent discovery in the platform narrative reflects a broader category change: governance can no longer stop at named administrators and service accounts. What matters is the full privilege graph, including delegated identities and runtime actors. Teams that have not mapped those paths will misjudge blast radius and understate governance gaps.

Privilege depth now matters as much as platform breadth. The market signal here is that vendors are being scored on whether they can sustain runtime relevance across diverse environments, not merely on whether they offer a vault or a session recorder. For practitioners, that means procurement should be tied to operational coverage, integration quality, and the ability to control privilege as an ongoing state. The buying test has become governance continuity, not feature count.

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 confidently map where privilege actually exists.
• The NHI Lifecycle Management Guide shows how provisioning, rotation, and offboarding have to work together if privilege is to stay bounded over time.

What this signals

Privilege governance is moving from static entitlement review to continuous control of runtime access. Teams that still separate PAM, IGA, and machine identity oversight will find that privilege issues surface too late, after access has already been granted or reused. The safer operating model is one where lifecycle, telemetry, and policy all point to the same authority layer.

Zero Standing Privilege will increasingly be the practical benchmark for modern PAM programmes. The organisations that can prove access disappears between tasks will have a cleaner audit story and a smaller attack surface than those relying on vaulting alone. The shift is especially important where service accounts and AI-driven workflows blur the line between human-admin and machine-admin privilege.

As machine and AI identities grow, the privilege graph becomes the control point. The question is no longer whether a tool can store secrets, but whether it can explain, limit, and retire every path that uses them. That is where procurement, architecture, and governance will increasingly converge.

For practitioners

• Reassess PAM as a runtime control layer Map every privileged decision point where access is granted, extended, or revoked during execution. Verify that JIT, session oversight, and policy enforcement reach SaaS, cloud, on-premises, and automation paths rather than stopping at the vault.
• Inventory standing privilege across machine and AI identities Identify service accounts, workload identities, and agentic access paths that retain privilege between tasks. Use those findings to separate true ephemeral access from centralised but persistent access.
• Test whether telemetry can spot active privilege misuse Validate that logs and alerts can distinguish expected automation from abnormal session behaviour in real time. If the signal only appears after the session ends, the control is too late for meaningful containment.
• Align PAM and identity governance around one control narrative Connect PAM policy, IGA review, and cloud entitlement management so the organisation can explain who has privilege, why it exists, and when it should disappear. This is especially important where over 600 integrations or multiple platforms create fragmented ownership.

Key takeaways

• AI-era PAM is being judged by runtime governance, not just secret storage or session recording.
• The market signal is clear: standing privilege across human, machine, and AI identities is now a board-level risk variable.
• Practitioners should measure whether privilege truly expires at task end, because centralised control without ephemerality is not enough.

Key terms

• Zero Standing Privilege: Zero Standing Privilege is an access model where no identity keeps persistent elevated access between tasks. Privilege is granted only when needed, for a defined purpose, and then removed automatically or through strict policy. It is especially important for machine and AI identities that can otherwise retain broad access indefinitely.
• Privileged Access Management: Privileged Access Management is the discipline of controlling, monitoring, and limiting high-risk access such as administrator accounts, service accounts, and delegated machine access. In practice, it combines vaulting, session oversight, just-in-time elevation, and policy enforcement so privilege is used only when the business need is present.
• Runtime Authorization: Runtime authorization is the decision to allow or deny access at the moment an action is about to occur, rather than only at login or provisioning time. For non-human identities, this matters because the risk often changes during execution, so static approval alone does not describe the true privilege state.

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: Delinea Named a Growth and Innovation Leader in Frost Radar™: Privileged Access Management 2026. Read the original.