This piece is by Ritesh Varma, Head of Business Consulting and Insurance Practice at Newgen Software.
Everyone in the insurance industry has their eyes set on the road ahead for AI in the sector. Will underwriting become autonomous? Will claims become touchless? Will servicing move predominantly to AI-powered channels?
Those are important questions, but they may not be the most critical ones. The bigger question is what happens after automation. Because if every insurer can automate underwriting, claims processing, fraud detection, and customer servicing, then none of those capabilities will remain differentiators for very long.
Insurers have seen this pattern before. Digital onboarding was once a competitive advantage. Today, it is an expectation. Self-service portals followed a similar trajectory. AI is likely to follow the same path. The insurers that create long-term advantage will be the ones looking ahead of the industry’s current AI conversation and preparing for what comes next. As artificial intelligence becomes embedded across the insurance value chain, competitive advantage will increasingly shift away from individual technologies and toward something less discussed: the ability to orchestrate decisions, systems, workflows, and customer experiences across the enterprise.
The Problem with Competing on AI Alone
Much of the present discourse around AI focuses on operational efficiency. Insurers are deploying AI to accelerate underwriting decisions, automate claims assessments, identify fraud patterns, and improve customer servicing. The value is undeniable; in fact, McKinsey’s analysis found that early AI leaders in insurance are already generating six times the total shareholder returns of their AI-laggard peers, and the gap is widening.
Yet efficiency alone rarely creates long-term differentiation. If two insurers can process a claim in minutes instead of days, the conversation quickly shifts elsewhere. Customers begin to evaluate them on transparency, responsiveness, and the overall experience. Technology becomes the baseline. Trust becomes the differentiator.
This is particularly relevant in insurance, where decisions carry significant financial consequences. Consumer support for AI has grown sharply, nearly doubling in a single year, but that support drops when AI moves from assisting humans to making autonomous decisions. The insurers that create lasting advantage will be those that combine AI-driven intelligence with experiences that strengthen trust, rather than simply accelerate transactions.
Where Most Insurers Actually Stand
Despite widespread interest, end-to-end workflow automation in underwriting or claims remains the least common AI deployment across the sector. Most insurers are still extracting value from narrower applications, chatbots, document summarization, point-in-process decision support, rather than AI that operates across connected workflows.
This is not a failure. It reflects a natural progression. The insurers pulling ahead are not simply asking where else they can add AI. They are redesigning entire journeys, submission to bind, quote to claim, renewal to service, so that intelligence flows across the enterprise rather than accumulates within isolated tools.
The mechanism enabling this shift has a name: agentic AI.
Unlike earlier applications that supported single-step decisions, agentic AI can plan and execute multi-step tasks with minimal human intervention. It does not simply generate a recommendation; it acts: triggering downstream workflows, coordinating across systems, and managing end-to-end processes autonomously while escalating exceptions to human judgment when needed. In 2026, agentic AI is the most actively pursued capability in the industry, with early production deployments emerging across underwriting, claims, and servicing.
But scaled deployment remains selective. The insurers extracting the most value from it are those that have done the harder foundational work first: consolidating decision logic, reducing system fragmentation, and building the operational infrastructure that agentic AI requires to function coherently. Agentic AI is not a shortcut to orchestration. It is the reward for having invested in it. Insurance Is Moving Closer to the Point of Need
The context in which orchestration matters is also shifting. Insurance is increasingly appearing within larger customer experiences — travel bookings, vehicle purchases, loan applications, and digital commerce. Rather than a standalone product, it is becoming part of the broader ecosystem in which customers already operate. Embedded insurance may appear simple to the customer, but delivering it requires coordination across multiple systems, partners, decisions, and channels in real time. That is fundamentally an orchestration challenge. And it is one that favors insurers who have built connected operational foundations over those still running disconnected pilots.
Local market intelligence continues to play a role here. Global insurers with sophisticated risk models are formidable competitors, but insurance decisions are shaped by customer behavior, distribution dynamics, and regional context that technology alone cannot replicate. Domestic insurers that combine institutional market knowledge with AI-driven decision-making are well-positioned to build more relevant products and more responsive experiences than those relying on either capability in isolation. Why Some Insurers Are Pulling Ahead
Many insurers are discovering that the biggest barriers to AI adoption are not the AI models themselves, but the operational complexity surrounding them. At one Indian life insurer, business rules remained embedded in the core system while underwriting processes relied on multiple disconnected applications. Rather than pursuing another automation initiative, the insurer focused on creating a unified decisioning environment that connected rules management, workflows, and operational processes. The shift enabled business and technology teams to work from a common decision framework, adapt more quickly to regulatory and market changes, and create a stronger foundation for intelligent, scalable operations.
The Next Phase of Transformation
Indian insurers have made substantial progress in adopting AI across claims, underwriting, fraud detection, and customer servicing. The next phase will be less about introducing new technologies and more about integrating them across the enterprise.
The industry has established that AI can make decisions faster. The more important challenge is ensuring those decisions move seamlessly across the organization, remain transparent, support regulatory requirements, and improve customer outcomes.
As agentic capabilities move from pilot to production, differentiation will no longer reside within individual processes. It will reside in how effectively insurers connect intelligence, operations, governance, and customer experience across the enterprise. The insurers that stand apart will not simply have more intelligent operations.
They will be the ones who recognized early that tomorrow’s competitive advantage would not come from AI alone, but from the ability to orchestrate it at scale. In a market where technology becomes increasingly accessible to everyone, the organizations that stay ahead will be those that lay the foundations for what comes next before the rest of the industry realizes it has arrived.
Be the first to comment