The next era of claims operations: From automation to autonomy

Claims represent a large part of insurer costs and remain a major contributor to the combined ratio. Yet despite years of sustained investment in core systems, analytics and automation, many organizations continue to experience rising loss adjustment expenses, variable cycle times, claims leakage and talent constraints.

These outcomes point to a structural gap and a deeper issue: modernization has digitized tasks but has not transformed decision authority, operating models, nor end-to-end orchestration.

Meanwhile, customer expectations, regulatory scrutiny and economic and social inflation are intensifying pressure on loss ratios, making incremental efficiency gains insufficient.

To move forward, insurers must look beyond optimization and reimagine how claims operations are fundamentally designed and run.

Research from the IBM Institute for Business Value shows 91% of insurance executives expect AI agents to deliver realtime optimization by 2027. 77% anticipate autonomous execution of transactional processes within 2 years. At the same time, 83% emphasize that human expertise remains indispensable.

The global market reflects this momentum. Research indicates that the insurance market is projected to grow from USD 8.13 billion in 2024 to USD 141.44 billion by 2034, a 33.06% CAGR.

The industry needs a pragmatic path that converts potential into measurable impact-reducing cost per claim, lowering loss adjustment expenses and improving the combined ratio.

Agentic AI introduces a new paradigm for claims operations. Instead of simply predicting outcomes or routing tasks, agents understand and interpret intent and context, execute decisions within defined guardrails, orchestrate actions across systems and continuously learn from results.

Empathetic AI capabilities enable agents to recognize emotional cues, respond appropriately in sensitive moments and support policyholders with clearer, more reassuring communication—especially during life events or high stress losses.

These systems empower adjusters by handling repetitive and data-heavy tasks while preserving human judgment for complex, nuanced decisions.

The result is an operating model that shifts from reactive processing to outcome-driven execution with continuous human oversight.

Most claim journeys still involve manual handoffs and disconnected systems. A balanced system powered by agentic AI helps close these gaps. It shifts competitive advantage from point productivity gains to end-to-end orchestration across people, processes and platforms. Consider these examples:

-      Life insurance: A beneficiary can submit a claim through email, text, web portal or contact center. Agents can then extract and validate documents, authenticate eligibility, screen for inconsistencies and assemble the case file. They can coordinate downstream payment steps and keep the beneficiary informed with clear, empathetic updates. Adjusters focus on judgment-driven and sensitive conversations where empathy and expertise matter most. This approach enables faster, more predictable benefit payouts at a time of loss, which reduces stress for beneficiaries when they are grieving and need support the most.

-      Property and casualty (P&C): After a homeowner submits storm damage photos, agents can classify the claim, validate the information, crosscheck policy data, flag potential fraud and produce a preliminary loss estimate. More agents can schedule vendors and update the policyholder on next steps. Exceptions move to an adjuster. This step shortens cycle time, reduces leakage, and lowers the cost per claim. As a result, policyholders receive faster damage assessments and repairs, helping them recover and return to normalcy sooner after a disruptive event.

Across both life and P&C, agentic AI strengthens decision quality, reinforces compliance and delivers more responsive support during critical events while keeping human expertise at the center of the claims experience. Insurers see the strongest results when these capabilities are anchored to clear constraints and applied with intent, rather than broad efficiency goals.

Agentic AI is already delivering measurable impact, including:

• Reduced cost per claim
• Accelerated cycle time
• Improved combined ratio through reduced leakage and faster, more consistent decisions
• Lower reliance on scarce adjuster talent without eliminating roles
• Scalable operations without linear headcount growth

These gains improve customer trust, employee experience and the insurer’s ability to provide consistent, personalized service at scale.

One recent example involved a client applying AI across a large life and annuity book to simplify and accelerate claims processing. By embedding AI across intake, validation and adjudication support, the organization has reduced friction for beneficiaries while improving the accuracy and consistency of downstream processing. The initiative illustrates how claims workflows can scale effectively across high-volume and highly regulated environments.

Agentic AI is becoming essential for insurers seeking financial resilience and operational agility. It enhances human expertise by enabling claims professionals to focus on complex decisions, sensitive conversations and higher-value work.

The question is no longer whether AI will reshape claims but how quickly insurers can convert ambition into action. Those who move decisively will improve cost performance, unlock and accelerate growth, and redefine the standard for what defines excellence in claims services.

Discover how IBM Consulting can help your organization reimagine claims operations with agentic AI