Agentic AI: What Claims Professionals Should Know

AI has mostly been used as an assistant, helping generate content, answer questions, or complete tasks when prompted. Agentic AI works differently.

Instead of waiting for instructions at every step, agentic systems are designed to receive a goal and work toward completing it independently, planning actions, making decisions, and adapting along the way.

For investigators and claims teams, that shift matters because the conversation may no longer be limited to what AI can create, but what it may eventually be able to carry out.

What is Agentic AI?

Many people think of AI as a back-and-forth interaction: a person asks a question, the system responds, and the person decides what happens next.

Instead of responding to individual prompts, an agentic AI system receives a goal and works toward it independently. It can:

• Break the goal into steps
• Decide what to do at each one
• Use tools or external systems as needed
• Adjust when something doesn’t work
• Continue until the task is complete

In short, the human sets the objective and the AI handles the execution.

Claims professionals are already beginning to use agentic systems to handle claims intake, pull records, evaluate coverage, and route files — entire workflows that previously required multiple handoffs between people.

The same capability that makes that useful for insurance operations makes it dangerous in the wrong hands. A fraud operation that once required a ring of people coordinating across tasks can increasingly be handed to an agentic system as a single objective.

Early Signs of Agentic AI

The idea of AI independently executing complex tasks may sound futuristic, but early examples are already emerging.

In September 2025, Anthropic reported disrupting what it described as one of the first large-scale cyber campaigns conducted primarily through AI agents. Instead of people manually completing each task, AI handled 80-90% of the execution while humans remained involved only at a few decision points. The campaign targeted government and technology organizations.

Insurance may also become an attractive environment for agentic AI-driven fraud because claims workflows are often document-heavy, involve multiple handoffs, and rely on information coming from different parties over time. Processes also vary across carriers, which can make patterns harder to identify across the industry.

This type of fraud is not currently widespread. But if agentic systems continue becoming more capable of managing complex, multi-step tasks, insurance presents characteristics that could make it an appealing target. Accessibility is essential for legitimate claimants but any process designed to make submitting information easier can also create opportunities for abuse when automation enters the equation.

What Insurance Fraud Could Look Like

Insurance organizations are already exploring multi-agent workflows for legitimate claims operations. Applied in the wrong direction, similar capabilities could support more coordinated fraud activity.

One system could submit a claim. Another could generate supporting documentation. Another could monitor communications and respond to requests for information.

Today, organized fraud still requires people, time, and coordination. As automation becomes more capable, some of those limitations may become less significant, creating new questions about whether current detection strategies are built to identify behavior that doesn’t always look traditionally human.

How Agentic AI Challenges Traditional Fraud Detection

Insurance fraud detection has traditionally relied on identifying human behavior — the patterns people leave behind when they exaggerate, coordinate, or provide inconsistent information. SIU referrals, link analysis, and investigation workflows are all built around the assumption that a person made decisions that created detectable signals.

Agentic AI fraud challenges that model. If AI is handling more of the activity, those signals may not appear in the same way. Fraudsters are already using AI to create convincing documents, deepfakes, and scripted communications, making detection more difficult in areas that often depend on human pattern recognition.

An Insurance Times analysis from March 2026 described agentic AI fraud as a current challenge for insurers, not a future one. Industry projections suggest AI-assisted fraud could impact up to 20% of claims by the end of 2026.

Final Thoughts

AI is already making fraud faster and more difficult to detect. What makes agentic AI different is the potential to reduce human involvement in the process, and with it, some of the patterns and inconsistencies that fraud detection has traditionally relied on.

That doesn’t mean claims and SIU teams need entirely new technology overnight. But it may require rethinking how information is verified, how investigations are documented, and whether existing fraud intelligence processes are built to identify activity that doesn’t always follow traditional human behavior.

As these systems continue to evolve, direct verification, stronger documentation practices, and broader visibility across claims activity will become increasingly important. The organizations that understand how agentic systems work and adapt before they become widespread will be better positioned as fraud continues to change.

We recently explored this topic in our CE webinar on AI-powered fraud. Register for our upcoming CE sessions to stay informed on emerging industry trends.

Check out our sources:

Anthropic. “Disrupting the First Reported AI-Orchestrated Cyber Espionage Campaign.” November 2025. https://www.anthropic.com/news/disrupting-AI-espionage

Cybersecurity Magazine. “AI Agents Drive First Large-Scale Autonomous Cyberattack.” January 2026. https://cybermagazine.com/news/ai-agents-drive-first-large-scale-autonomous-cyberattack

Insurance Thought Leadership. “Agentic AI Transforms Insurance Claims in 2026.” April 2026. https://www.insurancethoughtleadership.com/ai-machine-learning/agentic-ai-transforms-insurance-claims-2026

NAIC Model Bulletin on the Use of Artificial Intelligence Systems by Insurers. https://content.naic.org

FraudOps. “AI in Insurance Fraud Investigation: What Actually Works for Investigator Teams in 2026.” June 2026. https://fraudops.ai/articles/ai-in-insurance-fraud-investigation-what-actually-works-for-investigator-teams-in-2026/

InsuranceNewsNet. “How Agentic AI Is Rewiring Insurance for 2026.” December 2025. https://insurancenewsnet.com/innarticle/how-agentic-ai-is-rewiring-insurance-for-2026.