Many organizations think their biggest Zero Trust risk is a missed micro-segment or an unpatched firewall. In reality, risk often starts closer to the balance sheet: a bot posting journal entries, an AI agent updating customer records, or a “temporary” admin role no one removed. By 2025, many enterprises were already reporting dozens of non-human identities per employee, but far fewer controls on how those identities are governed.
On paper, the architecture is Zero Trust. In practice, identities are still over-privileged, under-governed, and hard to explain to auditors or the board. That’s the gap Identity Governance and Administration (IGA) must close, especially now that AI agents and other non-human identities are doing work humans used to do.
Centralized, policy-driven identity governance is now mandatory for any Zero Trust program, especially as AI agents and other non-human identities reshape how work gets done. Buying “Zero Trust” products without fixing identity governance is how CISOs end up explaining compliant breaches to their boards.
Why Zero Trust needs identity governance
Zero Trust architectures move security from static network boundaries to continuous decisions about every identity, every session, and every action. Frameworks like NIST SP 800‑207 center this on strong identity, granular policy enforcement, and continuous verification at policy decision and enforcement points.
Identity Governance and Administration (IGA) defines who should have access to which systems and data, under what conditions, and how that access is approved and monitored. Without mature IGA, Zero Trust controls rely on incomplete groups, stale roles, and opaque exceptions scattered across SaaS, ERP, and legacy systems.
You see the impact in real incidents and audit findings:
- Orphaned accounts in ERP that can still post journal entries months after an employee leaves.
- Privileged roles granted “temporarily” for projects, never revoked, and later used in unauthorized production changes.
- AI agents that are wired into CRM or ITSM with broad, static access because no one treated them as governed identities.
No matter how advanced your Zero Trust stack is, if the underlying entitlements are wrong, you are continuously “verifying” bad access.
What IGA actually does in a Zero Trust model
A modern IGA program gives Zero Trust something trustworthy to enforce by structuring how identities are created, governed, and retired. Core capabilities include:
- Lifecycle management: Automating joiner‑mover‑leaver processes so access aligns with role, policy, and real employment status.
- Policy‑based access: Defining who should have which entitlements under which conditions, then enforcing approvals, exceptions, and time limits through workflow.
- Access reviews and certifications: Asking managers and system owners to confirm whether access is still appropriate, with clear evidence for auditors.
- Segregation of duties (SoD): Detecting and blocking toxic combinations like “create vendor” and “pay vendor” on the same identity.
- Central visibility: Providing a single view of who — human or non‑human — has access to what across on‑premises and cloud systems.
Zero Trust engines then consume this governance data to drive real‑time decisions. When a role changes, modern IGA can automatically remove high‑risk entitlements, and Zero Trust policies reflect that change immediately rather than waiting for a quarterly review.
Recent State of IGA findings show that organizations with mature, automated IGA are more likely to report measurable progress on Zero Trust initiatives because identity and entitlement data is reliable enough to drive policy. As non-human identities grow, that dependency only increases.
The rise of non‑human identities and AI agents
Non-human identities (NHIs) such as service accounts, automation bots, workloads, and AI agents are multiplying faster than human accounts. Many organizations have dozens of non-human identities per employee, yet far less governance over how they’re created, used, and retired.
AI agents amplify this risk because they combine three properties:
- Scale: They can touch thousands of records or actions in minutes.
- Autonomy: They increasingly make decisions and execute tasks without direct human clicks.
- Opacity: Their behavior can be hard to reconstruct if logging, attribution, and identity are weak.
By early 2026, many large organizations already had AI agents in production, often tied into CRM, ERP, and collaboration platforms — but most were still struggling with formal governance of those agent identities. If you still treat AI agents like generic service accounts, you’re underestimating both their risk and their impact on your Zero Trust posture.
Industry guidance on non‑human identities emphasizes that NHIs must be discovered, classified, and governed as first‑class identities to reduce misuse and misconfiguration. Agentic AI simply raises the stakes on that advice.
From opaque service accounts to governed AI identities
Access governance for AI agents means replacing opaque, long-lived service accounts with governed, accountable AI identities. Instead of a tangle of tokens and technical users, each AI agent is:
- Onboarded as an identity with a named business owner, purpose, and defined scope.
- Granted least‑privilege access aligned to specific tasks, with SoD rules ensuring it cannot perform end‑to‑end fraud‑enabling flows.
- Given time‑bounded or just‑in‑time elevation for high‑risk actions, with Zero Trust policies checking context before granting.
- Continuously monitored, with activity attributed back to that identity and reviewed for anomalies.
In Zero Trust terms, you move from:
- Static, shared service accounts that no one really owns, to governed AI identities with clear sponsors, policies, and revocation paths.
- “Trust the agent because the vendor says it’s safe,” to “verify every action because the identity and entitlements are under your control.”
The AI identity challenge is increasingly described as a security team blind spot; extending access governance to AI agents is how you close that gap.
Identity Governance for AI agents inside IGA
Identity Governance for AI agents means bringing these identities into the same IGA program that manages employees, contractors, and partners, rather than creating a parallel AI track no one fully owns. Within IGA, you can:
- Define AI agents as a distinct identity type with tailored policies, approvals, and risk scores.
- Include AI agents in scheduled access reviews so business owners regularly validate their scope and necessity.
- Apply SoD rules to prevent agents from accumulating combinations of entitlements you would never allow a human to hold.
- Ensure decommissioned agents have credentials, keys, and tokens revoked as part of standard offboarding.
As agents act more autonomously on behalf of organizations, identity and governance become the primary control surface. Treating AI agents as governed identities inside IGA aligns Zero Trust principles with where actual risk now lives.
A brief real‑world example
Consider a global manufacturer that rolled out AI agents to triage IT tickets and update asset records in its ITSM platform. Initially, each agent ran under broad service accounts with admin‑level access “to keep things simple,” which triggered audit flags when the agents started modifying production configuration items.
By onboarding each agent as its own identity in IGA, assigning business owners, tightening entitlements, and including them in quarterly certifications, the firm cut high-risk AI entitlements by about a third while maintaining service levels. More importantly, auditors gained clear evidence of who approved which access, when it was last reviewed, and how Zero Trust policies enforced context around elevated actions.
How IGA strengthens Zero Trust day‑to‑day
When IGA and Zero Trust are integrated, daily operations become both safer and easier to defend:
- Faster deprovisioning: When an employee leaves or changes roles, their access — and any AI agents they sponsor — is automatically reviewed or revoked, reducing attack surface.
- Cleaner enforcement: Zero-Trust engines rely on accurate roles and entitlements rather than brittle, manually maintained groups.
- Audit‑ready evidence: IGA produces clear trails of who approved what, when, and under which policy, cutting time spent on access‑related audit findings.
- Reduced privilege creep: Regular certifications and SoD checks stop both human and AI identities from quietly accumulating dangerous combinations of rights.
Organizations using automated IGA consistently report fewer identity‑related audit issues and faster remediation cycles, particularly in complex SaaS and ERP estates. Those gains translate directly into stronger, more provable Zero Trust outcomes.
Quick self‑check: Are you really governing identities for Zero Trust?
Use these questions as a short internal diagnostic:
- Can you produce, in minutes, a single view of all high‑risk access — including AI agents and other NHIs — across your key systems?
- Can your auditors independently trace which human approved each AI agent’s access and when it was last certified?
- Do your SoD rules explicitly cover non‑human identities, or are AI agents and bots effectively exempt from conflict checks today?
- If an AI agent misconfigures a production system, can you reconstruct exactly which identity did what within a day, using standard logs and IGA evidence?
- When a sponsor leaves, are their AI agents automatically reassigned, reviewed, or decommissioned?
- Do your Zero Trust policies query up‑to‑date identity and entitlement data from your IGA platform, instead of relying solely on static groups or tags?
If you cannot confidently answer “yes” to most of these, your Zero Trust strategy has an identity governance gap.
Making IGA the control plane for Zero Trust
Zero Trust is ultimately a governance problem: who or what should be able to do what actions in which systems under which conditions, and how do you prove that to stakeholders? Identity Governance and Administration is the control plane that encodes those decisions and feeds them into your Zero Trust architecture.
As non-human identities and AI agents multiply, extending IGA to cover them as first-class identities is essential. Organizations that inventory NHIs, define policies for AI agents, and wire IGA data into their Zero Trust engines will be able to show boards and regulators that their Zero Trust strategy is real, measurable, and resilient in an AI-driven world.
If you’re reviewing your Zero Trust roadmap, start by asking whether your IGA program truly covers AI agents and non‑human identities, not just traditional users.
If you’d like to see what AI Governance looks like in practice, schedule a demo or set up a working session with our team to review your current identity governance gaps and possible next steps.
