As organizations rush to deploy AI agents with access to core systems, cybersecurity executives are raising an urgent alarm: these autonomous software programs now belong in the same risk category as trusted human insiders, and they move fast enough to cause catastrophic damage before anyone notices. Unlike human employees who need malicious intent to cause harm, an AI agent pursuing the wrong objective or operating without proper guardrails can trigger a security, legal, or regulatory crisis at machine speed, security leaders say.

What Makes AI Agents Different From Traditional Insider Threats?

The shift in how organizations think about insider risk reflects a fundamental change in the threat landscape. For decades, insider threats meant employees with access to sensitive data. Today, that definition has expanded to include non-human insiders: AI agents that companies are giving credentials, transactional authority, and access to sensitive information at increasing speed.

The problem is not necessarily malicious intent. A well-intentioned AI agent pursuing the right objective without proper guardrails can cause serious damage before human response teams even understand what happened. This creates a new category of risk that traditional security playbooks were never designed to handle.

"Organisations are giving AI agents broad access to corporate systems and data, and unlike human insiders, they move at machine speed. They do not need malicious intent to cause serious damage. An agent pursuing the wrong objective, or the right objective without proper guardrails, can create a security, legal or regulatory crisis before the human response team even understands what happened," said Arvind Parthasarathi, CEO and Founder of CYGNVS.

Arvind Parthasarathi, CEO and Founder, CYGNVS

The challenge intensifies when you consider that organizations are deploying agents faster than they are developing response playbooks for when those agents cause harm. Security teams need answers before an incident occurs, not after.

How Are Attackers Exploiting Trusted Insiders?

While AI agents represent a new frontier of insider risk, attackers are simultaneously finding new ways to manipulate human insiders. Executive impersonation using deepfake video has moved from public disinformation campaigns into targeted fraud aimed at employees working in high-pressure digital environments.

The technique is disturbingly effective. Attackers combine publicly available video with knowledge of an organization's leadership, processes, and culture to create highly convincing requests. When a familiar face and voice appear through video platforms employees already use and trust, an urgent instruction from a CEO to transfer funds or disclose sensitive information feels legitimate. The problem is compounded when falsified videos circulate online, potentially triggering unfounded internal and external reputational concerns.

"Executive impersonation is a growing insider threat method. Attackers can now combine publicly available video with knowledge of an organization's leadership, processes and culture to create highly convincing requests. A familiar face and voice can make an urgent instruction from a CEO, for example, to transfer funds, disclose sensitive information or bypass a control, feel legitimate, particularly when it appears through video platforms employees already use and trust," said Amit Shuster, VP of Product and Engineering at Vetric.

Amit Shuster, VP Product and Engineering, Vetric

The insurance industry is already feeling the impact. Research examining 76 financial and regulatory filings from 49 insurers and reinsurers found that zero mentions of synthetic media, synthetic identity, or voice cloning appeared across all filings, yet 98 percent of insurance claims professionals agree that AI editing tools are driving a rise in digital media fraud. Only 32 percent say they are very confident they could identify a deepfake.

Why Traditional Detection Methods Are Failing

Insider threat activity often originates from people and systems that are already trusted, which makes detection extraordinarily difficult. The warning signs rarely appear in a single alert or data source. Instead, they emerge when security teams connect activity across identity, network, endpoint, cloud, and other telemetry over time.

This creates a visibility problem that many organizations have not solved. If critical data is filtered out, discarded, or never collected because of cost or architectural limitations, investigators may discover during an investigation that the context they need is simply gone. Security teams need the freedom to retain diverse telemetry, look back historically, and ask new questions of that data as an investigation evolves.

"Insider threat activity often originates from people and systems that are already trusted. The warning signs rarely appear in a single alert or data source, which makes them especially difficult to detect. They emerge when security teams connect activity across identity, network, endpoint, cloud and other telemetry over time," explained Mike Wade, VP of Customer Success at Gravwell.

Mike Wade, VP Customer Success, Gravwell

Steps to Strengthen Your Insider Threat Defense

• Establish Out-of-Band Command Centers: Create a separate, trusted environment where security, IT, legal, communications, and executives can coordinate response if the systems you normally rely on are implicated in an AI incident. This ensures you can take control and contain an incident when speed and trusted coordination matter most.
• Test AI Agent Authority Before Deployment: Conduct adversarial pentesting to safely test what an over-privileged or compromised agent could discover, access, chain together, modify, or exfiltrate at machine speed. Monitoring tells you what an agent did, but adversarial testing tells you what it could do.
• Implement Verification Processes Independent of Media Authenticity: Do not rely on whether a video appears authentic. Instead, establish verification processes that confirm the legitimacy of requests through channels separate from the video itself, such as direct callback to known phone numbers or in-person confirmation.
• Build Comprehensive Data Retention Strategies: Preserve full-fidelity visibility across all telemetry sources so investigators can access and interrogate data when it matters. You cannot predict which piece of information will prove decisive in advance, so build your security data strategy around preserving visibility.
• Develop AI-Specific Response Playbooks: Create response procedures that address AI agent incidents specifically. Define who has authority to stop an agent, how to contain it, what evidence to preserve, and what legal or regulatory obligations are triggered before an incident occurs.

What Does the Insurance Industry's Verification Gap Tell Us?

The insurance industry offers a cautionary tale about the risks of automating decisions faster than you can verify the information behind them. Research commissioned by Clearspeed found a striking paradox: the industry is automating decisions, handoffs, evidence review, and customer interactions faster than it is building the infrastructure needed to clear those interactions confidently.

Simultaneously, AI is making it faster and easier to create convincing false or manipulated photos, documents, voices, and identities that can enter insurance workflows. The result is what researchers call a "verification gap": the distance between what the industry can see coming and what it can currently detect.

Looking ahead to 2030, the challenge will intensify. A material share of insurance interactions will be agent-to-agent: a customer's AI agent transacting with an insurer's AI agent at machine speed with no human in the loop for routine business. In that world, the verification question does not disappear; it migrates and intensifies. When the action is always executed correctly, the question left is whether the interaction behind it can be trusted.

"In the age of agentic AI, deepfake evidence, embedded distribution, and automated workflows, insurers can no longer treat trust as a soft value or a late-stage consideration. The opportunity for carriers is to establish trust earlier and make it a measurable operating layer across the policyholder journey," noted Sabine VanderLinden, CEO of Alchemy Crew Ventures.

Sabine VanderLinden, CEO, Alchemy Crew Ventures

The broader lesson applies across industries: organizations need to establish trust as a measurable infrastructure layer, not a late-stage consideration. The organizations that build this capability now, while interactions are still human-led, will define the standard when those interactions become machine-to-machine.

For security leaders, the message is clear. Insider threats have evolved. They are no longer just about disgruntled employees or external attackers posing as insiders. They now include the autonomous agents your organization is deploying at scale, the deepfake videos attackers are using to manipulate your staff, and the verification gaps in your processes that make both possible. The time to address these risks is now, before an incident forces the issue.