The potential impact of agentic AI in insurance claims

Unlike traditional AI models that require explicit instructions, agentic AI can act independently within defined parameters, learning from context and optimising outcomes without constant human intervention. In the realm of claims management, this capability could redefine efficiency, accuracy, and customer experience.

Claims processes often involve multiple handoffs, manual reviews, and reactive communication. Agentic AI introduces a shift by enabling proactive claims resolution. For example, when a policyholder reports a motor accident, an AI agent could:

• Initiate an instruction instantly upon notification from multiple sources, accelerating the time from notice to action.
• Authorise repairs or payouts within minutes, based on predefined risk thresholds.

This level of autonomy reduces cycle times dramatically, turning what used to be a multi-day process into a near-instant experience. ClaimPilot leverages agentic AI as it helps handlers to triage claims, validate policy details, and initiate settlement workflows faster and more accurately. In some cases, it has reduced claim cycle times by up to 40%, improving service for insurers and their customers.

Responsible adoption

While autonomy is powerful, human oversight remains essential. Agentic AI should not operate in isolation for high-stakes decisions such as large payouts or complex liability cases. By incorporating a human-in-the-loop approach, it ensures that adjusters review flagged claims, approve exceptions, and provide empathy where technology cannot. This balance of automation and human judgment builds trust and safeguards against errors.

Responsible adoption is paramount, which means not using AI for AI’s sake. Insurers should evaluate whether AI is the most efficient and sustainable solution for a given task. For example, if a simple rules-based workflow or lightweight automation achieves the same outcome with lower energy consumption, that should be the preferred choice. Davies applies this principle within ClaimPilot, deploying AI where it adds measurable value, while leveraging alternative solutions for routine processes to minimise environmental impact.

Orchestrating the customer journey

Fraud remains a significant challenge for insurance, costing billions annually. As an example of agentic AI’s potential impact, an agent can continuously monitor patterns across claims portfolios, flagging anomalies in real time. Unlike static rule-based systems, it adapts dynamically, learning from new fraud tactics and updating its detection models without waiting for human input. For example, if a claim involves inconsistent repair estimates or unusual location data, an AI agent can escalate it for human review before payment is authorised, saving insurers significant costs.

Agentic AI doesn’t just process claims; it orchestrates the entire customer journey. By integrating with IoT devices, telematics, and health trackers, it can anticipate needs before a claim is filed. Imagine a scenario where a connected home device detects water leakage: the AI could initiate a claim, schedule repairs, and update the customer, all without requiring them to lift a finger.

The road ahead

Agentic AI represents more than a technological upgrade, it’s a strategic enabler for insurers aiming to deliver faster, smarter, and more empathetic claims experiences. Our investment in ClaimPilot shows that this future is already taking shape. As adoption accelerates, those who embrace this innovation responsibly, balancing automation with human oversight and sustainability will set new benchmarks for efficiency and customer satisfaction in the insurance sector.