An employee with persistent, unsupervised admin access across critical systems, no audit trail, no clear owner, and no regular access reviews would raise immediate concern in most organizations. Yet non-human identities (NHIs) and AI agents are often granted that same kind of persistent, broadly privileged access. As AI adoption accelerates, this gap is becoming harder to ignore.

Understanding the Scale of the NHI Challenge

NHIs today encompass far more than traditional service accounts and API keys. They also include AI agents that make autonomous decisions, automated workflows with cross-system access, and shadow AI tools deployed by business users. The rapid proliferation of generative AI and agentic AI has expanded the attack surface dramatically. According to a recent Delinea survey, 87% of organizations report that their identity security posture is prepared for AI at scale. However, NHIs operate with speed and behavioral patterns that legacy controls were not designed to handle. IT teams are aware of the issue: 46% of those surveyed admitted that their AI identity governance is deficient.

This dissonance represents a risky double standard in enterprise security. On one hand, human identities are tightly controlled with password policies, multi-factor authentication, and regular access reviews. On the other hand, NHIs often enjoy unchecked privileges that can persist for months or years without oversight. This creates a significant blind spot that attackers are actively exploiting.

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 get 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 speed, fewer than one in three organizations enforce security requirements consistently. This trend is particularly alarming given that many AI pilots quickly transition into production systems without proper security reviews.

Poor Monitoring of Shadow AI

Unsanctioned agents operate outside any governance framework entirely. A significant 53% of surveyed organizations regularly encounter unauthorized AI tools and agents accessing company systems. These deployments bypass traditional provisioning processes, creating unmonitored access points that security teams struggle to detect and remediate. The rise of low-code and no-code platforms has further accelerated this shadow AI problem, as business users can now spin up AI agents without IT knowledge.

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. This means that once an NHI is provisioned, its activity often goes unmonitored until an incident occurs. The operational reality makes this challenge even more complex. According to the survey, 74% of organizations say standing access for NHIs and AI agents is necessary to meet uptime expectations, while 59% report they lack viable alternatives to persistent access.

The Operational Dilemma

Security teams are caught between the need for speed and the need for safety. They must support rapid AI adoption while also managing rising risks. The problem is compounded by the fact that many organizations do not even have a complete inventory of their NHIs. According to the same Delinea survey, fewer than one in three organizations actually validate NHI and AI agent activity in real time. Most IT decision-makers admit to at least some identity visibility gap, with NHIs representing the largest blind spot.

This lack of visibility leads to a false sense of security. Organizations might believe they are prepared because they have implemented some identity controls, but these controls are often designed for human users and fail to account for the unique behaviors of NHIs. For example, NHIs may make thousands of authentication requests per minute, far exceeding human activity patterns. Traditional security monitoring tools may not flag such activity as anomalous.

What Does Closing the AI Identity Risk Gap Require?

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. To close the gap, three steps are critical.

Step 1: Achieve Visibility

Before implementing new access controls or policies, 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, any governance efforts become guesswork rather than risk-based decision-making. Automated discovery tools that can map machine identities across cloud and hybrid environments in real time are essential.

Step 2: Implement 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%). Transitioning to zero standing privilege requires not only tooling but also cultural change within IT and operations teams. Gerry Auger, head of SimplyCyber, noted: "I'll count it as a win if we just have an inventory of all the identities that have standing access." This pragmatic view underscores how far most organizations still have to go.

Step 3: Enforce Rigorous Governance

Security teams must treat NHI access reviews with the same rigor applied to human access reviews. This includes regular certification and deprovisioning of unused accounts. Additionally, they should watch for NHIs requesting elevated privileges unexpectedly, as this often signals either compromised accounts or poorly configured automation. Flagging accounts with no clear owner or business justification for immediate review is another practical step.

Building Secure AI Without Slowing Innovation

You cannot halt AI adoption. The reality-based goal is closing the visibility gap that allows risky access patterns to persist undetected. Organizations need automated discovery tools that can map machine identities across cloud and hybrid environments in real time. Governance frameworks must operate at speed without the friction that drives teams to bypass strict oversight.

This requires upgrading identity infrastructure to handle the velocity and unpredictability of agentic AI. Security teams can satisfy business demands for speed without abandoning identity governance entirely. By starting with visibility, moving toward zero standing privilege, and enforcing rigorous governance, organizations can reduce the risk of NHI abuse while continuing to innovate.

The path forward is not simple, but it is clear. The first step is acknowledging that the double standard exists and committing to close the gap. As AI continues to reshape enterprise technology stacks, the organizations that invest in NHI governance today will be the ones that thrive tomorrow.

Source: Help Net Security News