AI-driven privileged access exposes the shadow privilege gap

At a glance

What this is: This is a CyberArk research-based analysis of how always-on privileged access, AI identities, and tool sprawl are creating a shadow privilege gap across modern environments.

Why it matters: It matters because IAM and PAM teams now have to govern privileged access across human, machine, and AI identities without relying on static assumptions that fail in dynamic environments.

By the numbers:

• 91% report that at least half of their privileged access is always-on, providing unrestricted, persistent access to sensitive systems.
• Only 1% have fully implemented a modern Just-in-Time privileged access model.
• 45% apply the same privileged access controls to AI agents as they do to human identities.
• 54% of organisations uncover unmanaged privileged accounts and secrets every week.

Context

Privileged access is the elevated access path that lets an identity administer systems, read secrets, or change critical settings. In this article, the problem is not just excess privilege, but the persistence of always-on access assumptions in environments where AI-driven identities and hybrid infrastructure change too quickly for static governance.

CyberArk's research frames that gap as 'shadow privilege', meaning unmanaged, unknown, or unnecessary privileged accounts and secrets that accumulate over time. The article argues that fragmented tooling, weak policy consistency, and inherited PAM models are leaving organisations with more privileged reach than they can clearly govern.

The central issue for identity teams is that modern environments now include human users, machine identities, and AI agents in the same privilege fabric. That makes privilege design, review, and control application a cross-domain governance problem rather than a PAM-only housekeeping exercise.

Key questions

Q: What breaks when privileged access is not continuously governed?

A: When privileged access is not continuously governed, standing privilege persists, dormant accounts remain usable, and the attack surface expands across human and machine identities. In practice, that creates a larger blast radius for credential theft and a weaker ability to prove who had access, when, and why. The result is operational drift, not just security exposure.

Q: How do AI agents change privileged access governance?

A: AI agents separate delegated human authority from machine execution, so the access record must show both. Teams should review what the agent can do on its own, what the user authorised, and which systems the agent can reach through API calls. That makes accountability clearer than treating the agent as if it were just another user.

Q: How do security teams know if shadow privilege is getting worse?

A: Look for a growing gap between the identities you can explain and the privileges you can actually enumerate. Frequent discovery of unmanaged accounts or secrets, repeated bypass of controls, and inconsistent policy application across tools are strong indicators. If reviewers need multiple systems to reconstruct who had access, the shadow privilege problem is already active.

Q: Should organisations prioritise just-in-time access over broad access reviews?

A: Yes, when the objective is to reduce active exposure rather than just document it. Access reviews tell you what exists, but just-in-time access changes how long privilege exists in the first place. For high-risk permissions, reducing standing access usually delivers faster risk reduction than another review cycle.

Technical breakdown

Why always-on privileged access breaks modern governance

Always-on privileged access means an identity keeps elevated permissions outside the specific task or session that needs them. That model was tolerable when workflows were slower and more predictable, but it becomes brittle when cloud, hybrid, and AI-driven systems change context continuously. The governance problem is not only exposure time, but the false assumption that standing privilege can be safely tolerated because it is administratively convenient. In practice, standing access widens blast radius and weakens attribution because the same credential can be reused across too many actions. Practical implication: treat standing privilege as an exception state, not an operating model.

Practical implication: move privileged access to task-scoped issuance and reduce the number of identities allowed to persist with elevated rights.

How shadow privilege accumulates across human, machine, and AI identities

Shadow privilege is the buildup of privileged accounts, secrets, and access paths that nobody can easily explain, own, or retire. It often appears when tooling is fragmented, when teams bypass controls to move faster, or when AI and machine identities are added faster than governance processes can classify them. The article shows that unmanaged privilege is not a rare edge case, because organisations report discovering it every week. That pattern matters because uncontrolled privilege is both a visibility failure and a lifecycle failure. Practical implication: inventory privileged identities by owner, purpose, and expiry condition before trying to optimise control depth.

Practical implication: create a privileged identity inventory that includes service accounts, secrets, and AI-driven identities, not just human admin accounts.

What fragmented PAM tools hide from reviewers

When multiple identity security tools cover different slices of access, reviewers can lose the full picture of who can do what, where, and under which policy. Fragmentation increases blind spots because one control plane may know about entitlement while another knows about session use, and neither gives a complete governance view. That makes access review slower, less reliable, and easier to bypass. The technical failure is not just tool count, but disconnected evidence across platforms, which undermines recertification and exception handling. Practical implication: reconcile privileged access data across platforms before relying on review workflows or policy assertions.

Practical implication: consolidate evidence sources for privileged access so reviews are based on complete entitlement and session data.

Threat narrative

Attacker objective: The objective is to convert unmanaged or persistent privileged access into broad administrative reach over sensitive systems and secrets.

1. Entry occurs when privileged credentials, secrets, or unmanaged access paths remain available outside a narrow task boundary, giving an attacker or over-empowered identity a persistent foothold.
2. Escalation follows when standing privilege or reused credentials allow broader actions than intended, including access to sensitive systems, configuration changes, or secret retrieval.
3. Impact is amplified when fragmented tooling and weak review discipline prevent rapid detection of who used the privilege, what was changed, and which downstream systems were exposed.

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 200+ breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

Shadow privilege is not a hygiene issue, it is a governance failure state. When organisations cannot explain why privileged access still exists, the problem is no longer just over-entitlement but a broken ownership model. That is why weekly discovery of unmanaged accounts and secrets should be read as a lifecycle signal, not an operational nuisance. The practitioner conclusion is that privileged access must be governed as a living inventory, not a static approvals file.

Always-on access is the wrong default for AI-driven identities. AI agents and machine identities change the meaning of privilege because they can act at machine speed and across more systems than a human reviewer can follow. Applying the same controls to AI and human identities treats two different runtime models as if they were identical, which weakens accountability and expands blast radius. The practitioner conclusion is that privilege policy must reflect runtime context, not identity label alone.

Persistent privilege assumes the window for review is longer than the task itself. That assumption holds only when access is stable enough to be observed, certified, and revoked on a predictable cadence. In dynamic cloud and AI environments, the review window often arrives after the privilege has already been used. The practitioner conclusion is that governance must move upstream to issuance time and task boundary, not downstream to periodic attestation.

Fragmented identity tooling creates shadow privilege faster than teams can reconcile it. When access, session, secrets, and policy data sit in separate systems, the governance picture becomes partial and delayed. That weakens recertification, slows remediation, and encourages bypass because controls feel disconnected from delivery needs. The practitioner conclusion is to design for control-plane coherence before adding more point solutions.

Identity blast radius: the real risk is not how many identities exist, but how much damage any one privileged identity can do before governance catches up. That concept is especially relevant when human admins, service accounts, and AI identities share the same privilege fabric. The practitioner conclusion is to measure privilege by reachable impact, not by account count alone.

From our research library:

• 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface, according to the Ultimate Guide to NHIs.
• 42% of machine identities have privileged access and 61% of organisations lack identity security controls for cloud workloads, according to CyberArk's 2025 Identity Security Landscape.
• Read next: Just-in-Time Access and Zero Standing Privilege Guide

What this signals

Shadow privilege is becoming a measurable operating condition, not a theoretical risk. The combination of persistent access, AI-driven identities, and tool fragmentation means teams should expect more unmanaged privilege to appear unless they design for issuance-time control rather than periodic cleanup. The right next step is to treat privilege as a runtime governance problem across human, machine, and AI estates.

Privilege reviews cannot compensate for broken access assumptions. When access is always on, the control is already late by the time certification begins. Security teams should watch for drift between policy intent and actual privilege scope, then redesign governance around task scope, ownership, and expiry rather than around the calendar.

For practitioners

• Define standing privilege as an exception state Map every privileged identity that can remain continuously active outside a named task, and require an explicit business reason for any exception.
• Build a unified privileged identity inventory Include human admins, service accounts, secrets, tokens, and AI-driven identities in one ownership and expiry register so reviewers can see the full privilege estate.
• Separate AI identity controls from human admin policy Set different approval, scope, and session assumptions for AI-driven identities instead of copying controls from human privileged access workflows.
• Reconcile access review evidence across tools Correlate entitlement, session, and secrets data from every identity security tool before certifying that privileged access is governed end to end.

Key takeaways

• Always-on privileged access is now colliding with AI-driven identity growth, turning privilege sprawl into a governance problem that PAM teams cannot solve with legacy assumptions alone.
• CyberArk's research says 91% of organisations still report that at least half of privileged access is always on, while 45% apply the same controls to AI agents as to humans.
• The practical response is to reduce standing access, distinguish AI identity governance from human admin workflows, and unify privileged visibility before reviews can be trusted.

Key terms

• Shadow Privilege: Shadow privilege is unmanaged or unnecessary elevated access that accumulates outside normal governance processes. It includes accounts, secrets, and entitlements that are unknown, poorly owned, or left active after their original purpose has passed, creating hidden pathways into sensitive systems.
• Standing Privilege: Standing privilege is access that remains active even when no immediate task requires it. For NHI programmes, it is a common failure mode because long-lived credentials and persistent roles create unnecessary exposure. Reducing standing privilege usually means tighter expiry, on-demand access, and clearer review of who or what still needs access.
• Just-in-Time Privileged Access Management: A control model that grants elevated access only for a defined task or session, then removes it automatically. In cloud environments, it reduces the time privileged credentials remain usable and makes misuse harder to sustain. The value depends on strong approval, logging, and revocation processes.
• Privileged Activity Review: The process of examining high-risk administrative actions to confirm they were authorised, necessary, and traceable. In VMware and SQL Server environments, this review depends on logs that connect configuration changes and management actions to accountable identities.

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.