Viewpoint: The Convergence of Autonomy and Intelligence Is Reshaping Insurance

The adoption of AI in insurance is a mixed bag, marked by ambitious experimentation on one hand and structural hesitation on the other.

The intent to deploy AI is high, and the expectations are rising just as quickly. Recent industry analysis indicates that the global AI in insurance market surpassed USD 10 billion in 2025, growing at a compound annual growth rate of over 30%. This growth underscores the accelerated pace at which insurers are investing in and adopting AI technologies across the value chain. Nearly 90% of insurers are actively evaluating generative AI, and over half (55%) have already implemented the technology in core functions such as claims, underwriting, and customer experience.

Insurers using advanced AI systems are reporting up to 75% faster processing speeds and up to 99% accuracy in risk assessments—a strong signal that predictive, intelligent automation is fast becoming a necessity rather than a discretionary capability.

Yet, AI adoption varies significantly. While some insurers are making substantive investments in this technology, others are adopting a conservative approach owing to concerns about legacy barriers, regulatory requirements, and workforce challenges. With generative AI promising a new wave of agentic systems, the divide must be narrowed, or insurers risk creating a two-speed industry in which operational leaders pull decisively ahead while others struggle with cost, speed, and relevance.

Multi-Agent Orchestration Across the Insurance Value Chain

For insurers, it’s imperative to move beyond task delegation to contextually aware, intelligent execution. With advances in natural language understanding, AI agents are evolving into intelligent partners that augment human ingenuity and expertise.

Multi-agent orchestration enables AI to move beyond isolated task automation toward coordinated, context-aware execution across the insurance value chain. Networks of specialist AI agents work in synchrony, governed by a collaboration layer that manages communication, data exchange, and work handoffs across systems and functions.

Across the insurance lifecycle, this orchestration delivers measurable impact:

• Policy proposals: AI agents segment applications, extract and validate data, and cross-reference inputs across historically siloed systems. Coordinated agent activity enables tailored offerings aligned to distinct customer personas and risk profiles.
• Compliance and policy management: Agentic AI operates alongside human expertise to monitor regulatory requirements, validate policy adherence, and manage updates with consistency and auditability.
• Claims management: AI agents interpret policy documentation and standard operating procedures, analyze images and loss data to assess impact, communicate with customers, and recommend adjudication outcomes. Human experts remain in the loop to review decisions and validate eligibility.
• Underwriting: Specialist AI agents simultaneously analyze large and diverse datasets to support risk assessment, pricing, and policy decisioning. Predictive models adapt dynamically as new data signals emerge.
• Customer servicing: AI agents deliver personalized, context-aware interactions that transform service engagements into ongoing relationship-building experiences.

Eliminating Fragmented Claims Handoffs Through Autonomous Orchestration

With its end-to-end autonomous workflows, agentic process automation eliminates manual touchpoints, significantly speeding up processing while maintaining high accuracy and consistency. Think of them as digital colleagues who are driven by the same goals that humans seek to achieve.

At the core of this autonomous orchestration is the ability to coordinate efficient action sequences across multiple systems without hiccups of data silos and delays in information gathering. AI agents enable intelligent triage and ‘best-action’ routing, making ‘near-instant’ resolution possible. Acting as an integration layer, agentic AI ensures that the team of human and AI agents operates on a single, unified source of truth in real-time. Its ability to learn continuously and adapt intelligently ensures that even exceptions and deviations are handled with ease. And all of this is done with an unerring ability to spot anomalies and fraud patterns with meticulous efficiency.

Dynamic Risk Assessment for Adaptive Pricing and Policy Management

Static risk assessment leads to the creation of generic insurance products. And here is where agentic AI makes a radical difference. Instead of leveraging historical data and rule-based systems, it adapts with agility to emerging risks across a vast canvas, including external data sources such as weather and geopolitical factors. Such use of real-time data results in a comprehensive risk assessment that provides a great competitive advantage.

External data sources can include inputs from connected cars or smart homes, social media, public records, regulatory bulletins, and more. From identity verification to potential indicators of fraud and changes in regulatory mandates, an ecosystem of multi-agent coordination can ensure that pricing, claims, and policy management synchronize with precision.

What This Means for Insurance Leaders

Agentic AI has catapulted the insurance industry to the edge of transformative change. With systems that can independently reason, make decisions and implement actions, dynamically learn from various outcomes, and adapt for continuous improvement in real-time, it has taken the industry forward at a rapid rate. Even better, it is doing so with empathy and personalization, thanks to its ability to analyze sentiments, behavior, and context.

That said, collaboration will be the critical glue. As insurers establish deep partnerships to build robust, interconnected systems, they must bear in mind that this is not a transformation for mere operational efficiency. There must be a fundamental reimagination of how insurance processes will be conceived, designed, and executed for a digital- and AI-first world. Players who dare to be bold in their purpose, thinking, and execution will create a powerful launchpad to stand at the forefront of innovation in the future.

The next phase of insurance leadership will belong to those who treat agentic AI not as a technology upgrade, but as a redesign of how decisions are made, risks are priced, and customers are served.