TL;DR: Gartner’s 2025 Market Guide for Identity Governance and Administration frames IGA around automation, AI-driven policy enforcement, and unified governance, while noting Pathlock as a representative vendor. The takeaway is that governance programmes now need to connect access control, compliance, and risk management more tightly than legacy certification cycles allow.
At a glance
What this is: This is Pathlock’s summary of Gartner’s 2025 IGA market guide, which says modern identity governance is shifting toward automation, AI-driven policy enforcement, and unified governance.
Why it matters: It matters because IAM and IGA teams now have to align access control, compliance, and risk management around faster governance decisions rather than rely on periodic review cycles.
Context
Identity governance and administration is the control layer that decides who gets access, who keeps it, and how that access is reviewed over time. Gartner’s 2025 market guide, as summarised by Pathlock, frames the category as moving beyond static certification toward more automated governance.
For IAM and IGA programmes, the practical issue is not whether access reviews still exist. It is whether they can keep up with the pace of cloud platforms, distributed entitlements, and policy changes that demand tighter connection between access control, compliance, and risk management.
Key questions
Q: How should IAM teams modernize IGA programmes for faster access change cycles?
A: They should move from periodic certification as the core control to a governance model that links policy evaluation, approval routing, and enforcement to live entitlement changes. The aim is not more review activity, but shorter time between access change and control action so policy remains current.
Q: Why do access reviews often fail to improve identity governance?
A: Access reviews fail when teams treat completion as success. If reviewers only confirm that an entitlement exists, rather than whether it should exist, the programme becomes a reporting exercise. Effective reviews remove unnecessary access, surface role drift, and trigger follow-up on exceptions that no longer match business need.
Q: What do teams get wrong about AI in IGA?
A: Teams often assume AI is only a productivity layer, when it may also influence or execute identity decisions. That creates accountability gaps unless organisations define which actions AI may recommend, which it may perform, and how every action is audited and reversed if needed.
Q: What does unified governance change for access, compliance, and risk ownership?
A: It forces these functions to operate as one decision loop rather than separate reporting tracks. That means IAM, compliance, and risk teams need shared criteria for exceptions, shared evidence for audits, and shared responsibility for remediation outcomes.
Technical breakdown
Why legacy certification cycles no longer carry the full governance load
Classic access certification assumes reviewers can inspect a relatively stable entitlement set at fixed intervals. That model breaks down when permissions shift faster than review cadence, or when governance must span multiple systems with different owners and approval paths. Modern IGA therefore has to do more than record decisions after the fact. It needs policy-aware automation that can route, enforce, and evidence access decisions while the entitlement state is still current.
Practical implication: Treat certification as one control in a wider governance system, not the point where governance begins and ends.
How unified governance changes the IGA operating model
Unified governance means access control, compliance evidence, and risk management are coordinated rather than handled as separate programme tracks. In practice, that shifts IGA away from being a reporting layer and toward being an operational control plane for access decisions. It also reduces the common gap where compliance teams can see exceptions but IAM teams cannot act on them quickly enough. The result is less drift between policy intent and actual entitlement state.
Practical implication: Design IGA workflows so policy exceptions, audit evidence, and remediation actions are connected in one operating loop.
Where automation and AI-driven policy enforcement fit
Automation in IGA is most useful when it shortens the delay between entitlement change, policy evaluation, and enforcement. AI-driven policy enforcement can help classify patterns, surface exceptions, and prioritise review queues, but it does not replace governance ownership or control design. If the rules are unclear or the data is poor, automation simply accelerates bad governance. The value comes from consistent decision-making at scale, not from removing accountability.
Practical implication: Use automation to scale governance execution, but keep policy ownership and exception approval explicitly assigned.
NHI Mgmt Group analysis
IGA is becoming an operational control plane, not a periodic review exercise. The market signal here is that governance now has to act continuously across access control, compliance, and risk management. That changes IGA from a backward-looking certification function into a live decision system that tracks entitlement state as it changes. Practitioners should judge tools and programmes on whether they close the gap between policy and enforcement, not just whether they generate audit artefacts.
Automation only helps when governance intent is already explicit. AI-driven policy enforcement can reduce manual friction, but it cannot fix undefined approval rules, inconsistent ownership, or weak entitlement data. In other words, automation amplifies the quality of the governance model already in place. Teams that automate before standardising policy will speed up inconsistency rather than reduce it.
The real IGA problem is entitlement drift across distributed environments. Unified governance matters because access decisions, evidence collection, and risk response are often fragmented across tools and teams. When those functions are separated, review outcomes do not translate into timely control changes. A modern IGA programme has to collapse that separation if it wants meaningful oversight.
Pathlock’s article reflects a broader market shift toward governance that is measured by action, not documentation. Mature programmes will be defined by how quickly they can detect access changes, route exceptions, and prove enforcement. That raises the bar for IAM leads, who now have to connect operational control, auditability, and business risk in the same governance design.
Modern IGA requires tighter linkage between policy decisions and lifecycle events. Access governance loses value when it is disconnected from joiner, mover, and leaver activity or from role and entitlement changes. The programme implication is clear: if governance cannot follow the lifecycle, it will always trail the risk it is meant to manage.
From our research library:
- Nearly 60% of IT leaders cite restrictive cost and complexity as a weakness of legacy identity governance, according to the 2025 State of Identity Governance Report.
- Read next: IGA Buyer's Guide
What this signals
Unified governance is now the useful shorthand for where IGA is heading. The programme challenge is no longer whether access can be reviewed, but whether review outcomes can be turned into control changes before the environment moves on. Teams that keep governance, compliance, and risk in separate workflows will keep producing evidence without reducing drift.
Automation should be judged by decision latency, not feature count. If an IGA process still depends on manual handoffs after policy exceptions are found, the governance model is already behind the environment it is meant to manage. That is the operating signal IAM leaders should watch most closely.
For practitioners
- Map governance decisions to entitlement lifecycle events Tie access approval, review, and revocation workflows to joiner, mover, and leaver changes so governance reflects current access state rather than stale review snapshots.
- Consolidate access, compliance, and risk workflows Design IGA processes so exceptions, evidence collection, and remediation sit in one operating loop instead of being managed by separate teams and tools.
- Use policy automation where rules are already clear Automate recurring governance decisions only after ownership, approval criteria, and exception handling are explicitly defined and tested against real entitlement data.
- Review certification cadence against entitlement volatility Check whether review intervals still match how quickly permissions change in cloud and SaaS environments, then adjust the governance model if they do not.
Key takeaways
- IGA is moving from periodic certification toward a more operational model that connects access control, compliance, and risk in one governance loop.
- Automation and AI-driven policy enforcement only improve governance when policy ownership, exception handling, and data quality are already clear.
- IAM teams should re-check whether their review cadence still matches how fast entitlements change across cloud and SaaS environments.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
NIST CSF 2.0, CIS Controls v8 and NIST SP 800-53 Rev 5 set the technical controls, while ISO/IEC 27001:2022 defines the regulatory obligations.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | GV.RM-01 — Risk Management Strategy | The article ties IGA to risk management and governance operating model design. |
| PR.AA-05 — Access Permissions, Entitlements and Authorizations | The article is fundamentally about governing access entitlements and review decisions. | |
| Recommendation — Align IGA operating decisions to an explicit risk management strategy and define how exceptions are escalated. Use entitlement governance controls to keep access decisions current and enforceable across systems. | ||
| CIS Controls v8 | CIS-5 — Account Management | IGA and certification processes sit directly on account and entitlement governance. |
| Recommendation — Review and revoke dormant or unnecessary access through a disciplined account management process. | ||
| NIST SP 800-53 Rev 5 | AC-6 — Least Privilege | The article’s access governance theme depends on limiting entitlement scope and ongoing privilege growth. |
| Recommendation — Apply least privilege to keep access within approved boundaries and reduce entitlement drift. | ||
| ISO/IEC 27001:2022 | A.5.15 — Access control | The article concerns access governance as an information security management concern. |
| Recommendation — Establish access control rules that connect approval, review, and revocation to business ownership. | ||
Key terms
- Identity Governance and Administration (IGA): A framework of policies, processes, and technology to manage and govern digital identities and their access rights. Increasingly extended to cover non-human identities alongside human users.
- Unified Governance Platform: A unified governance platform is a system that combines spend, risk, and control data into one reporting view. In practice, it reduces manual reconciliation and gives leaders a single operating picture for compliance, assurance, and investment decisions across the enterprise.
- Entitlement Drift: Entitlement drift is the slow accumulation of permissions that no longer match the original purpose, role, or workload. In cloud-native and NHI-heavy environments, it usually happens because access changes faster than review cycles, leaving organizations with more privilege than they intended.
- Policy automation: Policy automation is the use of rules and identity data to make access decisions and governance actions happen with minimal manual handling. In mature programmes it reduces delay and inconsistency, but it only works when the underlying identity records are clean and the policy model matches reality.
Deepen your knowledge
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Published by the NHIMG editorial team on June 24, 2026.
Updated on October 11, 2026.
NHI Mgmt Group, the independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org