For years, cybersecurity has had a familiar villain: the external attacker. The hacker breaking through the firewall, stealing credentials or exploiting an unpatched vulnerability. It is the scenario we have trained for, built defenses around and spent decades trying to prevent.
But the next major breach may not begin with someone breaking into your environment at all, it may begin with an AI agent that already has access. No black hoodie, no stacks of pizza boxes and spent energy drink cans, it may come from something we put on the network on purpose.
Imagine asking an AI agent to summarize support tickets while you grab lunch. A few minutes later it has searched multiple systems, queried customer databases, opened new tickets, updated records and sent emails, all without another human touching the keyboard. That is exactly why organizations are so excited about agentic AI. Agents are goal-oriented and largely autonomous, and this is why security teams should be paying close attention.
To do their job, agents must have valid credentials, API permissions and the ability to interact with email, cloud resources, SaaS applications, source code repositories, customer records, and internal documentation. In many organizations, these agents already have access to information that would make a traditional attacker jealous.
The troubling part is not that they have broken in, it is that they were invited.
The agent may not be malicious. It may not even be compromised in the traditional sense. Instead, it may simply be manipulated into taking actions that its creators never intended, while every identity system along the way sees nothing out of the ordinary. It is entirely possible that things can go awry not from the agent itself, but from an LLM hallucinating answers which then misdirect the next steps. Suddenly ChatGPT arguing wrongly about how many times the letter “R” is in the word “Strawberry” is not so funny, especially if it does the same with something important.
Welcome to the era of the non-human insider.
The Insider Has Changed
For years, insider threats generally fell into one of three categories: malicious employees, careless employees or legitimate accounts that had been compromised. Those risks are not going away. Humans are still remarkably good at clicking links they should not click, reusing passwords they should not reuse, and approving MFA prompts because they are in the middle of something else.
What is changing is the number of identities organizations now have to manage.
According to CyberArk's 2025 Identity Security Landscape report, machine identities now outnumber human identities by 82 to 1. The report also found that only 32% of organizations have the identity security controls needed to address AI-driven risks, while AI is expected to become the leading creator of new privileged identities during 2025. That is a fundamental shift that is going to need adjustments.
Organizations are no longer protecting only employees. They are protecting service accounts, workloads, automation platforms, integrations, bots, and increasingly, AI agents that can make decisions and carry out tasks on their own.
For years, the security question was simple:
"Is this the right user?"
Today the question is becoming much more difficult:
"Is this non-human identity performing an action that is appropriate, in the right context, for the right reason?"
That is a much harder problem to solve.
AI Agents Change the Risk
Traditional service accounts generally do exactly what they are programmed to do, but AI agents are different. The nature of agents means that rather than following a rigid sequence of instructions, they can plan multiple steps, choose which tools to use, summarize information, invoke APIs, generate code, update records, send messages or even delegate work to other agents. It is like having a new intern on the team, and while that is exactly what makes them valuable. But it is also what creates entirely new security concerns.
OWASP's Top 10 for LLM Applications identifies Prompt Injection as one of the most significant risks facing AI systems. It also highlights Excessive Agency, where AI systems are granted more authority than they should have, allowing them to interact with systems or perform actions that create unnecessary risk.
OWASP has also published its Top 10 for Agentic Applications, expanding on concerns such as goal hijacking, privilege abuse, memory poisoning, insecure communication between agents, and rogue agents.
The takeaway is fairly simple, once AI moves beyond answering questions and starts taking actions, the consequences change dramatically. A chatbot providing an incorrect answer may frustrate a user, but an AI agent that retrieves customer information, exports thousands of records, emails them externally and documents its own work has created a security incident that followed every instruction it believed it was supposed to perform.
The Numbers Are Already Concerning
This is not a future problem, it is happening now.
The Cloud Security Alliance reported in April 2026 that 82% of enterprises have AI agents operating in their environments that security teams either do not know about or do not fully understand. Nearly two-thirds of organizations reported experiencing at least one AI agent-related security incident during the previous year. Of those incidents, 61% involved data exposure, 43% caused operational disruption, and 35% resulted in financial losses.
The technology is advancing much faster than governance, identity management and monitoring practices.
Authenticated Does Not Mean Safe
One of the biggest challenges with AI agents is that they often appear completely legitimate. The agent logs in successfully, the credentials are valid, the API token works, the request comes from an approved application and the activity falls within its assigned permissions. From a traditional identity perspective, everything looks perfectly normal, but authentication and trust are not the same thing.
Security teams have spent years verifying identities. That remains important, but identity alone does not tell us whether an action is appropriate. An AI agent can be fully authenticated and still be manipulated into performing actions its owner never intended. This is already a problem we have been fighting with human accounts, and frankly have not had great success with.
Verizon's 2025 Data Breach Investigations Report found credential abuse involved in 22% of breaches, while third-party involvement doubled to 30%, highlighting how today's attackers increasingly abuse trusted identities instead of attacking network perimeters directly.
AI agents simply accelerate that challenge. Rather than stealing credentials, attackers may only need to influence the information an agent receives. Emails, documents, websites, tickets, repositories or chat messages may all become sources of instructions the agent interprets as legitimate. The identity remains trusted, but the decision does not.
How Organizations Create Non-Human Insider Risk
Most AI-related incidents do not happen because of a single mistake. They usually result from several issues coming together at the same time.
Persistent access
Long-lived API keys, OAuth tokens, service accounts and standing privileges give agents constant access long after it is needed.
Excessive privilege
Many agents can read, write, modify, approve, delete or deploy far more than their actual tasks require.
Untrusted input
Agents consume information from emails, support tickets, documents, chat conversations, websites and repositories. If attackers can influence those inputs, they may also influence the agent's decisions.
Limited behavioral monitoring
Many organizations can tell that an AI agent performed an action. Far fewer can determine whether that action actually made sense. Logging tells us what happened, understanding whether it should have happened is a different challenge altogether.
What Security Teams Should Do
The answer is not to ban AI agents.
That probably is not realistic, and in many cases, it would not make much business sense. AI can improve productivity, reduce repetitive work and help organizations accomplish tasks much more efficiently.
Like every technology before it, however, it needs appropriate security controls.
Start with visibility
You cannot secure AI agents you do not know exist. Organizations should maintain an inventory of deployed agents, identify who owns them, understand which systems they can access and document the actions they are allowed to perform.
Apply least privilege aggressively
If an agent only summarizes support tickets, it should not be able to modify customer records or access financial systems. Narrow permissions reduce the potential impact when something goes wrong.
Use temporary privileges whenever possible
Standing administrative access creates unnecessary risk for both humans and machines. High-impact actions should require additional approvals or time-limited access.
Monitor behavior instead of focusing only on authentication
Organizations need to understand what normal activity looks like for each AI agent. Which systems does it typically access? How much data does it usually retrieve? Which tools does it normally use? A valid identity behaving abnormally should still attract attention.
Require human approval for high-risk actions
Large data exports, financial transactions, privilege changes, production deployments, and customer-impacting decisions should include meaningful human oversight. The goal is not to slow everything down, it is to ensure someone verifies that significant actions make business sense.
Finally, build an offboarding process
AI agents do not always disappear when projects end. Forgotten agents with lingering credentials and unnecessary permissions create tomorrow's security incidents.
The Real Shift
The rise of the non-human insider does not replace human risk, it extends and expands it.
Humans still decide which AI tools to deploy. Humans assign permissions, configure integrations, approve access, and determine what information AI systems can reach. Those decisions now create digital identities capable of operating continuously, autonomously, and at a scale no employee ever could, and that is what changes the security conversation.
For years, we have focused on keeping attackers out, but increasingly, we will also need to ensure trusted identities behave the way we expect once they are already inside. AI agents are becoming another member of the workforce. Like any employee, contractor or privileged administrator, they need appropriate access, effective oversight and continuous monitoring.
Because in the age of agentic AI, the next insider may not be an employee at all, it may simply be an authenticated identity doing exactly what it was manipulated to do.
