An employee with persistent, unsupervised admin access across critical systems, no audit trail, no clear owner, and no regular access reviews would raise immediate red flags in most organizations. Yet non-human identities (NHIs) and AI agents are routinely granted that same kind of standing, broadly privileged access—often without any oversight. As AI adoption accelerates, this disparity is becoming a major blind spot in enterprise security.

NHIs today go far beyond traditional service accounts and API keys. They include AI agents that make autonomous decisions, automated workflows that span multiple systems, and shadow AI tools deployed by business users without IT approval. Each of these entities can request and hold credentials, permissions, and access rights, yet they operate with speed and behavior patterns that legacy identity controls were never designed to handle.

A recent survey of IT decision-makers highlights a troubling gap in perception versus reality. While 87% of organizations say their identity security posture is ready for AI at scale, nearly half admit that their AI identity governance is deficient. This cognitive dissonance represents a risky double standard that leaves enterprises exposed to credential misuse, lateral movement, and data breaches.

Why the NHI double standard exists

Three fundamental factors drive this double standard, each reinforcing the others to create a cycle of compromised identity governance.

Priority of speed over governance

Business pressure to deploy AI initiatives quickly means identity controls are often relaxed or skipped entirely. The survey found that 90% of organizations place pressure on security teams to loosen access controls to support AI-driven automation. When tension arises between security requirements and business velocity, fewer than one in three organizations enforce security requirements consistently. The result is a proliferation of over-permissioned NHIs that fly under the radar.

Poor monitoring of shadow AI

Unsanctioned agents operate outside any governance framework. More than half of surveyed organizations report regularly encountering unauthorized AI tools and agents accessing company systems. These deployments bypass traditional provisioning processes, creating unmonitored access points that security teams struggle to detect. Without visibility into shadow AI, organizations cannot assess the risk these entities pose.

Unchecked NHI activity

Traditional identity management systems rely on predictable, human-centric workflows. Legacy IAM tools lack the velocity and dynamic capabilities needed to govern autonomous agents that make independent decisions and request elevated privileges without warning. NHIs rotate workloads, scale elastically, and interact with other services in complex patterns that static policies cannot accommodate. As a result, standing access becomes the default, and audit trails remain incomplete.

The operational reality compounds the challenge. According to the survey data, 74% of organizations say standing access for NHIs and AI agents is necessary to meet uptime expectations. Meanwhile, 59% report they lack viable alternatives to persistent access for these accounts. This creates a situation where security teams knowingly accept risk under operational pressure.

What closing the AI identity risk gap requires

Organizations must confront the AI security confidence paradox. Expressing high confidence in AI readiness despite knowing there are fundamental governance gaps happens because information is incomplete. Security teams cannot protect against what they cannot see.

Consider this: 82% of organizations report confidence in their ability to discover NHIs with access to production systems, but fewer than one in three actually validate NHI and AI agent activity in real-time. The vast majority of IT decision-makers admit to at least some identity visibility gap, with NHIs representing the largest blind spot.

Step 1: Visibility

Before implementing new access controls, organizations must establish a clear inventory of which NHIs exist—including shadow AI use—what they have access to, and whether any of that access is standing or persistent. Without foundational visibility, governance efforts become guesswork rather than risk-based decision-making. Automated discovery tools that map machine identities across cloud and hybrid environments in real time are critical to this first step.

Step 2: Zero standing privilege

Just-in-time and ephemeral access represent the goal, even if they are not immediately achievable for most organizations. The survey shows organizations are more than twice as likely to use long-lived credentials (34%) compared to modern just-in-time authorization (16%). Shifting from standing to ephemeral access requires investment in tools that can issue, rotate, and revoke credentials dynamically based on context and risk signals. As one security expert noted, counting it as a win simply to have an inventory of all identities with standing access is a realistic starting point.

More practical governance tips

• Watch for NHIs requesting elevated privileges unexpectedly—this often signals either compromised accounts or poorly configured automation.
• Flag accounts with no clear owner or business justification for immediate review.
• Treat NHI access reviews with the same rigor applied to human access reviews, including regular certification and deprovisioning of unused accounts.

The scope of NHIs continues to expand as organizations embed AI into core workflows. Intelligent assistants, automated code deployment pipelines, data processing agents, and decision-making algorithms all require identity and access management that can match their dynamic nature. Without updates to identity infrastructure, the gap between perceived readiness and actual risk will only widen.

Security teams can satisfy business demands for speed without abandoning identity governance entirely. The path forward involves automated discovery, just-in-time authorization, and continuous validation of NHI activity. By treating non-human identities with the same scrutiny applied to human users, organizations can build secure AI environments that support innovation without exposing critical systems to unnecessary risk.

Source: Help Net Security News