Access management for AI agents is reshaping IAM priorities

At a glance

What this is: This is Ping Identity’s summary of its 2025 Gartner access management results, with a clear emphasis on machine access, AI agent identity, and verified trust.

Why it matters: It matters because IAM teams must now govern workforce, partner, machine, and emerging agentic identities in one access model without assuming human-centric controls still fit.

By the numbers:

• Ping Identity was named a Leader in the 2025 Gartner Magic Quadrant for Access Management for the ninth consecutive year.
• Ping Identity scored highest in three use cases in the 2025 Gartner Critical Capabilities for Access Management report.
• Only 5.7% of organisations have full visibility into their service accounts.
• NHIs outnumber human identities by 25x to 50x in modern enterprises.

👉 Read Ping Identity’s analysis of Gartner access management results and AI agent identity

Context

Access management is the control point where identity assertions, device trust, and authorisation decisions meet. In this post, the keyword is AI agent access management, because the article is really about how identity programmes are being evaluated across human, machine, and emerging agentic access patterns.

Ping Identity positions verified trust, orchestration, and machine access management as the next layer of access control. For practitioners, that signals a broader shift: the programme boundary is moving from employee SSO alone to delegated access, service identities, and agentic systems that act with more independence and broader blast radius.

Key questions

Q: How should security teams govern machine access as identity programmes expand?

A: Security teams should govern machine access with the same ownership, expiry, and revocation discipline used for other high-risk identities, but with stronger emphasis on non-interactive behaviour. The practical test is whether every service, API, or workflow identity has a named owner, a bounded purpose, and a clean offboarding path when the workload changes.

Q: Why do AI agents change access management requirements?

A: AI agents change access management because they can make runtime decisions, select tools, and continue actions without a human approving each step. That means authorisation can no longer be treated as a one-time permission grant. Teams need controls that bind action, scope, and accountability together throughout the session.

Q: What breaks when access reviews are built only for human users?

A: What breaks is the assumption that entitlements remain stable long enough to be observed, certified, and remediated. Machine and agent identities often do not follow that pattern. If reviews are still centred on periodic human attestations, teams miss short-lived privilege, delegated access, and non-interactive abuse paths.

Q: What frameworks should teams use for AI agent identity governance?

A: Teams should align AI agent governance with OWASP agentic application guidance, NIST AI risk management, and zero trust principles, while keeping NHI controls in view because agents depend on machine identities and credentials. The right approach is to govern the agent, the credential, and the execution boundary together.

Technical breakdown

Machine access management and delegated trust

Machine access management is the set of controls that govern non-human systems such as services, APIs, workloads, and tokens. Unlike human access, machine access often runs continuously, exchanges credentials programmatically, and depends on trust established outside a browser or interactive session. That makes auditability, scoping, and revocation more important than login experience. When vendors score this use case highly, they are signalling that enterprises are trying to unify policy for both interactive and non-interactive access paths. The operational challenge is not only authentication. It is lifecycle control over identities that may never log in, never reauthenticate manually, and never appear in traditional access review workflows. Practical implication: treat machine identities as governed subjects, not invisible plumbing.

Practical implication: map machine identities to named owners, expiry, and revocation paths before they proliferate beyond review.

Verified trust for AI agent identity

Verified trust moves identity from assumed legitimacy to explicit proof across user, device, and action. In an agentic context, that matters because an AI agent may select tools, invoke APIs, and continue execution without a human click at every step. The identity problem is no longer just who authenticated, but what was authorised to do, when, and under whose accountability. That changes how privilege is modelled, because the useful control is not only access assignment but execution boundary. If organisations treat AI agents as enhanced service accounts, they miss the behavioural difference: agents can chain actions and change scope mid-session. Practical implication: tie every agent action to a provable identity and a bounded execution context.

Practical implication: bind every agent action to a bounded execution context, not just an authenticated principal.

Orchestration, API access control, and identity blast radius

Orchestration does not remove identity risk. It concentrates it. When access is federated across apps, APIs, partners, and automated workflows, a single weak policy decision can propagate across many systems. API access control is especially relevant because APIs are the control surface where machine and agent identities actually consume privileges. The real issue is identity blast radius, which grows when the same access pattern is reused across multiple constituencies without differentiated governance. Strong orchestration should reduce friction, but it also needs tighter segmenting of entitlement scopes, stronger token hygiene, and clearer offboarding paths. Practical implication: reduce reuse of broad tokens and standardise revocation before scaling orchestration further.

Practical implication: reduce broad token reuse and standardise revocation before expanding orchestration further.

Threat narrative

Attacker objective: The objective is to turn a trusted non-human or agentic identity into a scalable access path that reaches more systems than its original assignment should allow.

1. Entry occurs through authenticated access granted to a machine or agent identity that can operate across connected systems and APIs.
2. Escalation happens when delegated permissions, broad tokens, or orchestration paths let that identity reach beyond the original intended task scope.
3. Impact follows when the identity can influence multiple systems quickly, increasing blast radius across data, workflows, or downstream access paths.

Breaches seen in the wild

• Moltbook AI agent keys breach — Moltbook breach exposed 1.5M AI agent keys.
• AI LLM hijack breach — attackers used stolen AWS access keys to hijack Anthropic LLM models on Bedrock.

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

NHI Mgmt Group analysis

AI agent access management is becoming the new test of whether access control still reflects runtime reality. The article’s emphasis on machine access management and agentic AI identity shows that access programmes are being judged against identities that do not behave like human users. That means policy, scope, and revocation now have to survive machine speed and delegated execution. Practitioners should read this as a governance shift from login control to execution control.

Verified trust is only useful when identity and action stay bound together. The article points to verified trust as a future state, but the deeper issue is that access decisions lose value if they are not attached to a specific action context. In agentic and machine-driven environments, identity can be valid while the action is no longer aligned with the original intent. That makes accountability and authorisation inseparable. Practitioners should treat action provenance as part of access governance.

Machine access management is still being undercounted in most identity programmes. The NHI baseline shows why: only 5.7% of organisations have full visibility into their service accounts. When visibility is that low, leadership claims about complete access governance are overstated. The implication is that access management maturity must be measured by what is owned, visible, and revocable across human and non-human estates.

AI agent governance collapses the old assumption that access can be reviewed after the fact. Access review processes were designed for stable entitlements and human-paced certification. That assumption fails when an autonomous actor can gain, use, and discard access within one session, leaving no durable review state. The implication is that governance teams must rethink the review model itself, not just add more controls around it.

Identity blast radius is the right concept for this market shift. The combination of orchestration, machine access, and agentic identity means the unit of risk is no longer the individual credential alone. It is the range of systems that one identity can reach, influence, or destabilise through delegated trust. Practitioners should measure access programmes by blast-radius containment, not by seat counts or login convenience.

From our research:

• 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface, according to Ultimate Guide to NHIs.
• Only 20% have formal processes for offboarding and revoking API keys, and even fewer have procedures for rotating them.
• As teams move toward agentic access governance, compare that baseline with Ultimate Guide to NHIs , Lifecycle Processes for Managing NHIs to see where offboarding and revocation still break down.

What this signals

Identity blast radius is the practical lens this post should trigger in IAM programmes. As more organisations extend access management to machine and agent identities, the key question becomes how far one credential can move before governance notices. That is a different problem from user login friction, and it should be measured separately in policy reviews and entitlement design.

With NHIs outnumbering human identities by 25x to 50x in modern enterprises, machine access management is no longer an edge case. The programme implication is straightforward: if your governance model still starts with human accounts and then adds non-human identities as exceptions, your control plane is already behind the estate.

For teams formalising zero trust around automated access, 90% of IT leaders say properly managing NHIs is essential for a successful zero-trust implementation. The signal is not that zero trust is incomplete, but that its access assumptions become fragile when machine identities are allowed to scale faster than lifecycle governance.

For practitioners

• Inventory machine and agent identities separately Create distinct registers for workforce, partner, service, and agent identities so governance, ownership, and review cadence are not collapsed into one access catalogue.
• Bind access to explicit action context Require that high-risk machine and agent permissions include task scope, session purpose, and revocation conditions rather than broad reusable entitlements.
• Rework access reviews for non-human estates Move review evidence toward ownership, expiry, and actual usage signals for service accounts, APIs, and agent credentials instead of relying on human certification patterns.
• Standardise revocation across orchestration paths Make deprovisioning and token revocation part of the same workflow across APIs, workflows, and partner access so delegated access cannot outlive its business purpose.
• Adopt a blast-radius control metric Track how many systems a single machine or agent identity can reach and use that number to prioritise entitlement reduction, token tightening, and segmentation.

Key takeaways

• Access management is shifting from human-centric sign-in control to broader governance of machine and agent identities.
• The biggest risk is not just authentication failure, but excessive privilege and weak lifecycle control across non-human access paths.
• Practitioners should measure blast radius, ownership, and revocation quality before scaling orchestration or agentic access further.

Key terms

• Machine Access Management: Machine access management is the governance of non-human identities that authenticate and act automatically, such as services, APIs, workflows, and tokens. It focuses on ownership, scope, expiry, and revocation because these identities may never sign in interactively or pass through human review cycles.
• Verified Trust: Verified trust is an access model that requires explicit proof before an identity, device, or action is accepted. In non-human environments, it matters because valid authentication alone is not enough. The action itself must be tied to a bounded context and a clear accountability chain.
• Identity Blast Radius: Identity blast radius is the amount of systems, data, and workflows a single identity can reach if its credentials or permissions are abused. The term is especially useful for non-human and agentic environments because one credential can propagate across many systems far faster than a human user can.
• Delegated Access: Delegated access is permission granted to one identity to act on behalf of another identity, user, or process. In IAM and NHI governance, it becomes risky when delegation is broad, long-lived, or poorly revocable, because accountability and control can separate from the original business purpose.

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 Ping Identity: the 2025 Gartner access management results and their implications for AI agent identity. Read the original.