​​Target the right processes for agentic AI success in insurance​

In insurance, the pressure to do more with less has never been greater. Customers expect faster service, greater transparency and more personalized engagement, while insurers must manage rising operational costs, an aging workforce and an increasingly complex regulatory environment.

Agentic AI is emerging as a practical response to these pressures. By combining perception, reasoning and autonomous action, it enables systems to make context-aware decisions and complete tasks from start to finish with minimal human input. Besides speeding up claims processing, it also leads to more consistent, data-driven outcomes that improve efficiency and strengthen customer trust.

As with any technology, however, value depends on focus. Real value comes from applying agentic AI to high-volume, data-intensive processes — the core operational areas that make or break daily performance.

Claim processing: Improving speed and accuracy

Claims processing is on of the most resource-intensive areas of insurance. From first notice of loss to settlement, every step involves data collection, validation and decision-making. These are precisely the types of activities where agentic AI delivers measurable improvements.

AI agents can gaher documentation, verify details across systems and flag anomalies before human review. They can also identify litigation propensity and potential fraud patterns early in the process to avoid unnecessary payouts and deliver faster, fairer resolutions. AI agents can also compile a personalized plan for loss mitigation by considering a range of risk factors and historical data points.

Insurers that have implemented agentic AI in claims are reporting up to 90% faster first-notice-of-loss processing, a 20%–25% reduction in adjusting expenses and improved customer satisfaction scores. These outcomes illustrate how automation, when designed responsibly and applied in the right places, can improve both operational performance and policyholder experience.

Underwriting: A new level of precision

Underwriting is another area where agentic AI can transform performance. Traditional underwriting relies on manual review and interpretation of data from multiple internal and external sources — and it’s typically a slow process.

By introducing agentic AI, insurers can automate manual tasks such as submission intake, third-party data collection, triage and agent communication to reduce effort by as much as 60%. More importantly, they can:

• Use knowledge agents to retrieve, summarize and analyze relevant information in real time
• Deploy advanced, adaptive risk-scoring models
• Build simulations
• Conduct what-if analyses

These agents support human underwriters by providing context-aware insights, surfacing comparable cases and highlighting anomalies that require expert judgment. The result is greater speed, consistency and accuracy. Productivity gains of over 150% have been observed in some implementations, with decision quality improving alongside efficiency.

Rather than replacing underwriters, AI augments their expertise so they can focus on complex assessments that demand experience and intuition.

Fraud detection and risk management: Smarter protection

Fraud is a persistent challenge in insurance, costing billions annually. Rules-based systems can only go so far — they often produce false positives or miss subtle patterns of suspicious behavior.

Agentic AI takes fraud prevention further by analyzing millions of data points —claims histories, behavioral trends, even contextual signals like timing or location— in real time to detect irregularities that would be impossible for humans to identify consistently.

Because these agents can reason and act autonomously, they can prioritize the highest-risk cases for investigation, improving accuracy and reducing wasted effort. In doing so, they help insurers achieve stronger loss ratios and operational resilience.

Customer service: Scaling personalization

Modern insurance customers expect fast, frictionless service with a human touch. Meeting that expectation at scale is difficult when service teams are stretched across channels and time zones.

Agentic AI enables a new service model that blends automation and empathy. Conversational AI agents can handle common queries, process simple policy changes or guide customers through claims submission. They deliver consistent, accurate responses instantly, allowing human agents to focus on high-value interactions that require nuance and care.

Insurers deploying these solutions have seen tangible results: Fewer escalations, shorter resolution times and measurable Net Promoter Scoreimprovements. By combining automation with human oversight, they maintain the trust and transparency central to every insurance relationship.

IT and operations: Building resilient foundations

Behind every insurer’s promise to their customers is a complex network of systems, processes and technologies. Keeping that ecosystem stable and efficient is critical, and it’sanother area where agentic AI is proving invaluable.

Self-healing operations use AI agents to monitor infrastructure, detect anomalies and trigger corrective actions automatically. They can resolve routine issues before they disrupt service, improving uptime and reducing the workload on IT teams.

Agentic AI can also support software development and testing, speed up release cycles and improve code quality. Benchmarks show cycle-time reductions of up to 30% and fewer post-release defects, which translate directly into faster delivery of new digital products and services.

Embedding governance from the start

As adoption grows, governance remains the key to sustainable success. The insurance industry operates in one of the most tightly regulated environments in the world, and AI must meet the same high standards of fairness, transparency and accountability.

Global regulation is evolving quickly. The EU AI Act sets a comprehensive framework for governance and traceability. In North America and Asia, more flexible approaches are encouraging innovation but still emphasize responsible use. Across all regions, insurers must ensure that every AI-enabled decision can be explained, monitored and audited.

NTT DATA helps insurers embed these principles from the outset. Our AI Enablement Framework integrates governance, security and compliance at every stage of development and deployment, allowing clients to innovate confidently while maintaining trust with regulators and customers alike.

Accelerating transformation with the right partner

Agentic AI is reshaping the insurance value chain, but technology alone does not create transformation. Real progress comes from disciplined execution, clear governance and the right partnerships.

We work with our clients to translate AI potential into measurable outcomes. Drawing on our deep industry expertise, regulatory insight and proprietary AI tools, we help themprioritize the highest-value opportunities and implement them responsibly at scale.

This is how insurers will move beyond experimentation and build a lasting competitive advantage by implementing efficient, resilient and trusted AI.

WHAT TO DO NEXT

Read the NTT DATA ebook, Agentic AI in insurance: Accelerating efficiency, customer experience and growth, to explore where agentic AI is already making a measurable difference and how it can be applied in your organization.