Gen 3 PAM reframes privileged access for machines and AI

At a glance

What this is: NHI Mgmt Group's analysis, drawing on Akeyless's blog post: Gen 3 PAM must cover humans, machines, workloads, APIs, and AI agents rather than only human administrators.

Why it matters: IAM and PAM teams need to reassess standing privilege, secret lifetime, and access governance because machine-scale and AI-driven access patterns break assumptions built into legacy PAM models.

By the numbers:

• Up to 85% of identities in many environments are now machines, services, containers, pipelines, and AI agents rather than humans.
• Over 50% of organizations have experienced a security incident tied to compromised machine credentials.

👉 Read Akeyless's analysis of Gen 3 PAM for machines and AI

Context

Privileged Access Management is the control plane for elevated access, but that control plane was designed around human administrators and static infrastructure. In cloud-heavy, automated environments, the subject is no longer just who can log in, but which identities can obtain, hold, and reuse privileged capability across machines, workloads, APIs, and AI agents.

Akeyless frames Gen 3 PAM as the response to that shift: standing privileges, persistent secrets, and human-only governance no longer match how access is actually consumed. The article's core claim is that modern PAM has to be built around ephemeral access and unified identity coverage, not around long-lived credentials and manual review cycles.

For IAM and PAM programmes, the practical question is whether privileged access is still being governed as a person-centric problem. If machines and AI agents now represent a major share of privileged activity, then lifecycle, audit, and least-privilege controls have to operate at machine speed as well as human speed.

Key questions

Q: What breaks when PAM only covers human administrators?

A: A human-only PAM model leaves service accounts, workloads, and AI-connected systems outside the same governance discipline. Those identities can still perform privileged actions, but they often bypass human approval, lifecycle review, and session oversight. That creates hidden privilege paths that are harder to audit and revoke.

Q: Why do exposure management programmes struggle in cloud and automation-heavy environments?

A: They struggle because cloud assets, service accounts, and secrets change faster than ticket-based review cycles. If context is stale by the time remediation begins, the programme is managing old evidence rather than current exposure. Continuous validation and tighter identity correlation are needed to keep decisions aligned with runtime reality.

Q: How should security teams govern privileged access across service accounts and AI-driven systems?

A: Security teams should govern privileged access by focusing on the actions an identity can perform, not only on the account it uses. That means short-lived credentials, task-scoped permissions, clear ownership, and real-time policy decisions. Without those controls, service accounts and AI-driven systems accumulate standing privilege that is difficult to review or safely revoke.

Q: Should organisations treat PAM, secrets management, and key management as separate programmes?

A: No. Separating them creates blind spots because the same operational workflow may depend on privileged access, application secrets, encryption keys, and certificates at once. A unified governance model is easier to audit and better matches how modern infrastructure actually consumes identity and privilege.

Technical breakdown

Why standing privilege fails in dynamic infrastructure

Standing privilege means an identity retains ongoing access after the task that required it has finished. In traditional PAM, that model was tolerable because admins were the dominant privileged actors and sessions were relatively discrete. In cloud and automation-heavy environments, however, access is increasingly consumed by workloads, service accounts, pipelines, and AI systems that act continuously or intermittently at runtime. The result is a wider exposure window, more reused credentials, and weaker assumptions about when privilege should start and stop. When privilege is persistent, compromise is not tied to a single session; it can be replayed, sold, or reused long after the original use case ends.

Practical implication: Treat standing privilege as the exception and require explicit expiry logic for every privileged identity class.

How zero-standing privilege changes credential mechanics

Zero-standing privilege shifts access from pre-provisioned credentials to just-in-time issuance. That means the identity receives only the privilege needed for the current task, and the credential is meant to disappear immediately after use. This is not just about rotation cadence. It is about removing durable access state from the default operating model so that compromise yields little reusable value. In practice, this requires ephemeral secrets, secretless authentication paths where possible, and policy enforcement that binds access to context, duration, and scope. For machine identities, that pattern is closer to runtime authorization than to traditional vaulting.

Practical implication: Design privileged workflows so that credentials are issued on demand and cannot persist beyond the approved task window.

What unified identity coverage means for humans, machines, and AI agents

Unified identity coverage means the PAM layer is not siloed by actor type. Human admins, service accounts, APIs, and AI agents all need to be governed under the same access policy model, even if the authentication method differs. That matters because modern infrastructure often combines these identities in one workflow: a human triggers automation, a workload fetches a secret, and an AI agent decides when to invoke a tool. If each is governed separately, privilege becomes fragmented and auditability weakens. A modern PAM architecture therefore has to coordinate access control, secrets management, and lifecycle governance across the full identity chain.

Practical implication: Map every privileged workflow end to end and govern the full delegation chain, not just the visible human step.

Threat narrative

Attacker objective: The attacker wants durable privileged access that survives the original use case and can be reused to reach infrastructure, secrets, or AI-driven workflows.

1. Entry occurs when an attacker obtains a standing secret, reused credential, or other durable privileged artifact from the machine identity estate.
2. Escalation follows when that credential can be reused across workloads, environments, or administrative paths without immediate expiry or contextual binding.
3. Impact is broad because persistent machine privilege allows reuse, resale, or lateral movement long after the original task or session should have ended.

Breaches seen in the wild

• Azure Key Vault Contributor escalation 2024: Datadog found Azure Key Vault Contributor could add itself to access policies and read every secret, key and certificate in a vault.
• BeyondTrust breach 2024: A stolen BeyondTrust Remote Support API key let a China state-sponsored actor reset accounts and reach US Treasury workstations in 2024.

Read and download The State of NHI & AI Agent Breach Report 2026, covering 150+ breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

Standing privilege is now a machine-scale governance failure, not a human convenience issue. Legacy PAM assumed privileged access would be issued to a person, observed in a session, and then certified or revoked. That assumption breaks when machines, workloads, and AI agents operate continuously across environments and do not fit a human review cadence. The implication is that privileged governance has to move from session review to issuance-time control.

Ephemeral access is the new control boundary for privileged identity. When access exists only for the task and disappears immediately after use, the attack value of compromised credentials collapses. That shifts the decisive control from vault storage to issuance policy, context, and expiry enforcement. Practitioners should stop treating password rotation alone as the answer to machine privilege risk.

Unified identity security is becoming a PAM requirement, not an architecture preference. The article correctly links privileged access, secrets, encryption keys, certificates, and AI agent access as one operational problem. Those layers now share the same blast radius, so fragmented tools create blind spots in governance and audit. The practitioner conclusion is that the identity control plane must cover all privileged actors together.

Machine and AI access reveal the runtime governance gap. Privilege review cadences were designed for access that persists long enough to be certified. That assumption fails when a workload or AI agent acquires and releases privilege within the same operational cycle. The implication is that identity programmes must rethink what is being governed: not just entitlement at rest, but entitlement at the moment of use.

Gen 3 PAM is a category signal for the wider identity market. The direction of travel is away from human-only PAM and toward policy-driven control of every privileged identity type. That validates the move toward ZSP, workload identity governance, and AI agent authorisation as core programme capabilities. Practitioners should expect PAM roadmaps to converge with broader identity security architecture.

From our research library:

• 59% of organisations say they lack viable alternatives to standing privileged access for NHIs and AI agents, according to Delinea research.
• Read next: Ultimate Guide to NHIs — Key Challenges and Risks

What this signals

Ephemeral privilege is becoming the practical boundary for modern PAM. The important shift is not whether access exists, but how quickly it expires once the task is complete. Programmes that still depend on durable secrets for workloads or AI-driven automation will keep inheriting avoidable blast radius, especially when identity sprawl crosses human and non-human estates.

Standing privilege debt: access that remains valid after the task it supports has ended is now the central governance smell in cloud-first environments. That debt is visible whenever organisations can describe their human admin model but cannot explain how machine or AI privilege is issued, bounded, and removed in the same control framework.

For practitioners

• Map privileged access by actor type Inventory human admins, service accounts, workloads, APIs, and AI agents separately, then trace where each one acquires elevated access, how long it persists, and who can revoke it.
• Replace standing secrets with task-scoped issuance Prioritise ephemeral credentials for workflows that do not require persistent access, and remove any default privilege that survives beyond the task or session.
• Bind access to context and expiry Require policies that enforce time-bound, context-aware issuance for elevated access, especially where automation or AI-driven execution can outpace human review.
• Unify audit trails across privileged identity layers Correlate privileged access, secrets usage, key access, and certificate lifecycle events in one governance model so the same workflow is not audited in separate silos.

Key takeaways

• Legacy PAM falls short when the privileged actor is a machine, workload, or AI system rather than a human administrator.
• The article says more than half of organisations have already seen incidents tied to compromised machine credentials, which shows the problem is operational rather than theoretical.
• The control shift is toward zero-standing privilege, short-lived issuance, and governance that spans every privileged identity layer.

Key terms

• Zero Standing Privilege: A control model in which an identity does not keep persistent access unless it is actively needed. For NHIs, this means credentials and permissions are issued for a narrow task and then removed. It reduces the time window and reuse value of stolen access.
• Ephemeral secret: A credential or token that exists only for a short, task-specific window. In identity security, ephemeral secrets are used to reduce replay risk, limit blast radius, and prevent long-lived access from becoming a standing attack surface.
• Machine Identity: The digital identity of a machine, device, or workload, such as a server, container, or VM, used to authenticate it within a network. Sometimes used interchangeably with NHI, though NHI is the broader category.
• Privileged credential governance: The policies and operating controls that govern high-risk credentials such as tokens, API keys, and application secrets. Effective governance covers issuance, rotation, revocation, ownership, and auditability so that access can be removed cleanly when a vendor incident occurs.

What's in the full article

Akeyless's full article covers the operational detail this post intentionally leaves for the source:

• The generation-by-generation PAM breakdown, including what Gen 1 and Gen 2 PAM handled well and where they break down
• The architecture claims behind Zero-Knowledge protection and Distributed Fragments Cryptography™ in the Akeyless model
• The product-level description of unified privileged access, secrets management, encryption, and certificate lifecycle handling
• The enterprise validation example involving a cloud-heavy infrastructure provider and the evaluation criteria used

👉 The full Akeyless article covers the PAM evolution model, Gen 3 requirements, and enterprise validation details.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity lifecycle 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.