If 2025 was the year the industry aggressively deployed agentic AI to automate everything from code deployment to customer service, 2026 is shaping up to be the year we pay the security debt for that speed. We have effectively built an "AI-native" enterprise ecosystem, but in doing so, we have introduced a new class of insider threat that doesn't sleep, doesn't take breaks, and crucially doesn't think like a human.
We are now facing the "Triple Threat": a convergence of Agentic Risk, Identity Governance Deficits, and a massive Visibility Gap. The consensus is clear: while we have been busy giving AI agents the keys to the kingdom, we haven't built the locks to keep them in check.
Agentic Risk: The "Super-User" Problem
The first component of this threat is Agentic Risk. In our rush to enable autonomy, organizations have inadvertently created a legion of digital "super-users." To ensure these agents can complete complex workflows without interruption, IT teams often grant them excessive administrative privileges. The result is "risky automation" that can turn a simple configuration error into a catastrophic data breach.
This isn't just a theoretical problem. Recent observations across the security landscape highlight a disturbing disconnect where IT professionals admit they do not fully understand the security implications of the AI policies they are tasked with enforcing. When your defenders don't understand the rules of engagement for your digital workforce, you don't have a policy; you have a gamble. If an attacker compromises an agent with admin rights, they don't need to hack your network; they just need to ask your agent to open the door.
The Identity Governance Deficit: Running a Sprint in a Marathon
The second vector is the Identity Governance Deficit. The fundamental issue here is that our current Identity Governance and Administration (IGA) frameworks are designed for humans, not machines. We have rigorous processes for onboarding employees, conducting quarterly access reviews, and offboarding leavers. In contrast, AI agents often operate outside this lifecycle entirely, spinning up dynamically to meet workload demands and frequently retaining access long after their specific task is complete.
This creates a dangerous blind spot where non-human identities accumulate toxic levels of entitlement without any human oversight. Leadership teams across multiple sectors identify this inability to effectively govern machine identities as a primary barrier to securing their AI operations. Federal guidance often points to frameworks like NIST[1] to establish a baseline for identity management, but unless these are adapted to account for the ephemeral and high-velocity nature of AI identities, organizations risk losing control over who, or what, has access to their most critical data.
The Visibility Gap: You Can’t Secure What You Can’t See
The final, and perhaps most immediate, danger is the Visibility Gap. For years, our industry has preached that "identity is the new perimeter." Yet, when it comes to non-human identities, that perimeter is effectively invisible.
Reports from agencies such as the Cybersecurity and Infrastructure Security Agency (CISA) have long emphasized the critical nature of logging and monitoring to detect anomalies[2]. Despite this, a significant number of organizations effectively have no way to track the data access and usage behaviors of their autonomous agents. We are flying blind. These agents are accessing sensitive datasets, moving laterally across networks, and executing changes, often without leaving an audit trail that legacy SIEM tools can contextualize. This invisibility doesn't just facilitate external attacks; it creates an environment for insider threats where the "insider" is a rogue or compromised line of code.
The Verdict: Verify the Verifiers
As we navigate 2026, the "set it and forget it" mentality for AI deployment must end. The solution isn't to stop automating, as that ship has sailed, but to treat AI agents with the same "Zero Trust" scrutiny we apply to human employees.
This means implementing strict Role-Based Access Control (RBAC) for every digital identity, enforcing the principle of least privilege so that no agent has more power than strictly necessary. It means moving toward adaptive governance models that use AI to monitor AI, closing the speed gap between action and oversight. And finally, it demands investing in monitoring technologies that can illuminate the "Visibility Gap," giving security teams real-time insight into what their digital workforce is doing.
The "Triple Threat" is real, but it is solvable. The only question for 2026 is whether we will lead our AI agents, or let them lead us into a crisis.
EMA™ released research on Agentic AI identities in 2025, and is scheduled to release its report “Navigating the Identity Crisis: A Data-Driven Analysis of IGA Maturity, Risks, and Future Roadmaps” in 2026, which will explore this topic further.
[1] https://www.nist.gov/identity-access-management
[2] https://www.cisa.gov/resources-tools/resources/best-practices-event-logging-and-threat-detection
