IGA vs. PAM in modern IAM: where governance and control diverge

At a glance

What this is: This is a comparison of Identity Governance and Administration and Privileged Access Management, with the key finding that they solve different parts of the IAM problem.

Why it matters: For IAM and NHI practitioners, the practical question is not which tool is stronger, but where lifecycle governance ends and privileged control must begin.

By the numbers:

• 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface.
• Only 20% have formal processes for offboarding and revoking API keys, and even fewer have procedures for rotating them.
• 70% of organisations grant AI systems more access than they would give a human employee performing the exact same job.
• Only 44% of organisations have implemented any policies to manage their AI agents, despite 92% agreeing that governing AI agents is critical to enterprise security.

👉 Read StrongDM's guide to the difference between IGA and PAM

Context

Identity governance and privileged access are often discussed together, but they answer different questions. IGA governs who should have access, while PAM controls how elevated access is issued, monitored, and revoked. For NHI governance, that split matters because service accounts, API keys, tokens, and AI agents behave more like privileged operational identities than ordinary users.

StrongDM frames the difference through a conventional enterprise lens, yet the same boundary now applies to machines and agents. A security team that treats all non-human access as one category will miss the separate problems of lifecycle control, elevation, and auditability. That is increasingly a governance gap, not just a tooling preference.

Key questions

Q: How should organisations split responsibilities between IGA and PAM?

A: Use IGA to govern identity lifecycle, role assignment, certification, and access policy across the enterprise. Use PAM to control elevated access at runtime through vaulting, session oversight, and just-in-time privilege. For NHIs, the split is essential because lifecycle ownership and privileged execution are separate risks, even when the same system contains both.

Q: What is the difference between just-in-time access and identity governance?

A: Just-in-time access is a privilege delivery pattern that reduces how long elevated access exists. Identity governance is the broader discipline of defining who or what should have access, when it should be reviewed, and when it should be removed. JIT can lower exposure, but it does not replace ownership, certification, or offboarding discipline.

Q: Why do non-human identities complicate zero trust design?

A: Non-human identities complicate zero trust because their access is often automated, high frequency, and distributed across cloud, CI/CD, and agentic workflows. Zero trust assumes continuous verification, but verification is weak if the identity inventory is incomplete or if credentials are embedded in code. The control problem is lifecycle and delegation as much as authentication.

Q: When should security teams prioritise PAM over broader identity governance?

A: Prioritise PAM when the immediate risk is privileged execution, such as accounts that can modify systems, access production data, or change infrastructure. Prioritise broader identity governance when the larger problem is incomplete inventory, weak ownership, or missing offboarding. For most NHI programmes, both are needed, but the order depends on where the highest blast radius sits.

Technical breakdown

How IGA governs identity lifecycle and access policy

IGA is built around the full identity lifecycle: provisioning, role assignment, access requests, certification, attestation, and removal. Its strength is governance at scale, because it can answer whether a user or workload should still have access at all. For NHIs, that model becomes tricky when identities are created automatically, embedded in pipelines, or tied to ephemeral workloads. The core issue is that governance workflows designed for humans assume stable ownership and periodic review. NHIs rarely behave that way. Practical implication: map every machine identity to an owner, purpose, and review cadence before relying on IGA controls alone.

Practical implication: define ownership and review cadence for every NHI before expecting IGA to govern it.

How PAM controls privileged access at runtime

PAM focuses on elevated access, usually by vaulting credentials, enforcing step-up authentication, recording sessions, and issuing just-in-time privileges. In practice, PAM does not solve identity lifecycle across the enterprise. It reduces the blast radius of high-risk access by making privileged actions temporary, visible, and auditable. For NHIs, PAM becomes relevant when a token, service account, or automation path can modify systems, databases, or cloud infrastructure. The limitation is that PAM can only control what it can broker. If secrets are already scattered across code, CI/CD, or unmanaged tools, runtime monitoring arrives too late. Practical implication: use PAM to constrain dangerous execution paths, not to discover missing identities.

Practical implication: use PAM to constrain dangerous execution paths, not to discover missing identities.

Where IGA and PAM overlap for NHI governance

The overlap is in policy enforcement and audit evidence, but the control objective differs. IGA determines whether access is appropriate over time. PAM determines whether elevated access is safe right now. For NHI programmes, that means one system should handle inventory, ownership, and certification, while the other handles secrets vaulting, session control, and ephemeral privilege. The mistake is to assume one can substitute for the other. That assumption breaks down quickly in cloud and agentic environments where access is dynamic and service accounts often outnumber humans by orders of magnitude. Practical implication: split governance and execution controls, then integrate their audit trails.

Practical implication: split governance and execution controls, then integrate their audit trails.

Threat narrative

Attacker objective: The objective is to turn unmanaged non-human access into durable control over systems, data, or cloud operations.

1. Entry occurs when a service account, API key, or automation credential is created outside governed lifecycle controls and later reused in production.
2. Escalation happens when that credential has broader permissions than the task requires, allowing the attacker or rogue process to reach administrative functions.
3. Impact follows when the privileged credential is used to alter systems, move laterally, or extract sensitive data without timely detection.

Breaches seen in the wild

• Moltbook AI agent keys breach — Moltbook breach exposed 1.5M AI agent keys.
• Cisco DevHub NHI breach — IntelBroker exploited exposed Cisco credentials, API tokens and keys in DevHub.

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

NHI Mgmt Group analysis

IGA and PAM are complementary controls, but they solve different failure modes in NHI governance. IGA answers whether an identity should exist and what it should access over time, while PAM answers how risky access is controlled at the moment of use. For NHIs, that distinction is no longer academic because service accounts and AI agents often operate with broader operational reach than human users. Practitioners should treat lifecycle governance and privileged execution as separate control planes.

Ephemeral access does not eliminate trust debt if the underlying identity model is weak. Just-in-time access reduces standing privilege, but it does not fix poor ownership, weak inventory, or misplaced credentials in code and CI/CD. In practice, short-lived access can still be over-broad if policy design is lax. The field needs to stop equating temporary access with safe access. Practitioners should measure privilege scope, not just credential duration.

NHI governance is increasingly a delegation problem, not just an authentication problem. Humans can sign in, but machines and agents act on behalf of processes, pipelines, and business functions. That means accountability depends on who authorized the action, what scope was granted, and whether the access can be revoked cleanly. The IGA and PAM split helps, but only if organisations can tie each non-human action back to a sponsor and purpose. Practitioners should build delegation records into identity governance now.

The governance gap is widening as non-human identities outnumber humans and move faster than review cycles. IGA controls built for periodic review struggle when identities are created dynamically and used continuously. PAM reduces exposure for elevated actions, but it does not substitute for inventory, lifecycle, or offboarding discipline. This is the core operating problem for NHI programmes. Practitioners should align tooling to the identity's behaviour, not the organisation's org chart.

From our research:

• 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface.
• Only 20% have formal processes for offboarding and revoking API keys, and even fewer have procedures for rotating them.
• That gap points directly to the need for NHI Lifecycle Management Guide discipline before organisations lean on runtime controls alone.

What this signals

Identity governance teams should expect more of the NHI control burden to move into runtime policy. As machine identities and AI agents become more operational, the old review cycle model will not keep up with the pace of credential creation and privilege use. Organisations that still treat NHI access as a quarterly audit problem will keep missing the real exposure window.

Ephemeral access will become a baseline expectation, not a differentiator. The programme question is no longer whether teams can issue temporary privilege, but whether they can prove ownership, delegation, and clean revocation across service accounts, tokens, and agents. That is where governance debt accumulates fastest.

With 70% of organisations granting AI systems more access than human employees in the same role, per the 2026 Infrastructure Identity Survey, the IAM model is already under strain. Teams should prepare for policy designs that distinguish human approval from machine execution and preserve traceability across both. That is the next practical step in NHI control maturity.

For practitioners

• Define separate control objectives for IGA and PAM Map IGA to identity lifecycle, access certification, and ownership. Map PAM to privileged execution, session monitoring, and just-in-time elevation. Do not allow one control family to stand in for the other when reviewing NHI risk.
• Inventory all non-human identities by function and privilege Classify service accounts, API keys, tokens, certificates, and AI agents by owner, system, and privilege level. Prioritise identities that can modify infrastructure, access sensitive data, or act across multiple environments.
• Remove standing privilege from machine identities Replace persistent elevated access with task-scoped access wherever possible. Pair that change with session logging and approval paths for any workflow that still needs elevated actions.
• Tie every non-human action to a sponsor Require a named human owner for each NHI and record which system or workflow approved its access. That delegation record should be part of certification, audit, and offboarding workflows.
• Audit secret storage outside governance systems Search code repositories, CI/CD tools, config files, and ad hoc vaults for secrets that bypass identity governance. Close those paths before relying on monitoring or certification to control exposure.

Key takeaways

• IGA and PAM solve different parts of the same identity problem, and NHIs expose that separation more clearly than human access does.
• Excess privilege and incomplete offboarding remain the main reasons non-human access turns into enterprise risk.
• Practitioners should align governance, runtime control, and delegation evidence before treating any machine identity as low risk.

Key terms

• Identity Governance And Administration: Identity Governance and Administration is the part of IAM that manages who or what should have access, how that access is approved, and when it is reviewed or removed. For NHIs, it becomes the control layer for ownership, lifecycle, certification, and audit evidence across service accounts and automation identities.
• Privileged Access Management: Privileged Access Management is the control set that limits and monitors elevated access. It usually includes vaulting, session recording, step-up authentication, and just-in-time privilege. For NHIs, PAM matters when a token, key, or service account can change systems, data, or infrastructure at production scope.
• Just-In-Time Access: Just-in-time access is a pattern for issuing privileged credentials only when a task requires them, then revoking them after use. It reduces standing privilege and shrinks the attack window, but it does not replace identity ownership, policy design, or offboarding discipline for machine identities.
• Non-Human Identity: A non-human identity is any digital identity used by software, workloads, bots, or AI agents rather than a person. These identities authenticate, request access, and act in systems, but they often outnumber human users and can carry broader privileges, longer lifetimes, and weaker oversight.

Deepen your knowledge

IGA, PAM, and NHI lifecycle governance are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are building a control model for service accounts, tokens, or AI agents, it is worth exploring.

This post draws on content published by StrongDM: IGA vs. PAM: What’s the Difference? Read the original.