BriteCore’s 2026 Annual P&C Core Systems Report reveals a striking convergence between the operational areas insurers most want to improve and where they see the greatest potential for generative AI. When asked about their operational priorities, 72% of insurance professionals identified streamlining underwriting workflows, while another 72% pointed to optimizing claims processing. When asked where they see opportunities to apply Gen AI, underwriting and claims again rose to the top, cited by 67% and 65% of respondents, respectively.

The alignment is difficult to ignore. The industry’s biggest productivity challenges and its leading AI opportunities are increasingly centered on the same workflows. AI is moving beyond a standalone technology initiative and becoming part of how insurers expect core insurance workflows to operate.

Underwriting: Reducing the Burden of Knowledge Work

Underwriting has always been information intensive. Underwriters gather information from submissions, policy data, documents, third-party sources, prior interactions, and other systems before determining whether a risk fits an insurer’s appetite and how it should be priced. Core system technology has automated parts of that process for years, but much of an underwriter’s work still involves finding, reviewing, interpreting, and synthesizing information.

This is where AI introduces a new productivity opportunity. Rather than simply automating a predefined step, AI can help underwriters work more effectively with the information surrounding a risk. It can summarize submissions, surface relevant policy and risk information, identify missing data, and provide decision support within the underwriting process.

The objective is not to remove the underwriter from underwriting, but to reduce the repetitive knowledge work surrounding the decision so underwriters can focus their expertise where it matters most. Greater underwriting productivity can help carriers evaluate opportunities faster, improve consistency, and support growth without creating an equivalent increase in operational complexity.

Claims: Turning Information Into Action Faster

Claims presents a similar opportunity. Adjusters routinely work across claim details, policy information, notes, documents, correspondence, estimates, and other data while determining what happened and what should happen next.

Traditional workflow automation in a policy admin system can route a claim, assign a task, or trigger an action when predefined conditions are met. AI can complement those capabilities by helping adjusters understand and act on the information flowing through those workflows. It can summarize claim histories, surface relevant information, reduce manual review, explain complex information, and help identify the next steps requiring attention.

For insurers, the opportunity is to increase productivity while preserving the human oversight and judgment that complex claims require. That becomes increasingly valuable as carriers look to improve service, manage expenses, and handle greater volumes without adding equivalent operational complexity.

From Workflow Automation to Intelligent Workflows

Underwriting and claims illustrate a broader change in insurance technology. Traditional automation is highly effective when the process and rules are known: when a specific event occurs, the core insurance system performs a predefined action. Those capabilities remain essential, but AI expands what technology can contribute.

AI can work with unstructured information, provide context, summarize complex data, assist with decisions, and increasingly coordinate activities across multiple steps of a process. Instead of sitting alongside insurance operations as a separate tool, intelligence can become embedded directly within the workflows employees already use.

That is where the productivity equation begins to change. The opportunity is no longer simply people + more automation. Increasingly, it is people + modern core workflows + AI.

Each component plays a distinct role. People provide expertise, judgment, and accountability. Core systems provide the data, business rules, workflows, permissions, and transactional foundation of insurance operations. AI adds intelligence that can help people interact with that foundation more efficiently. Together, they create the potential for insurers to accomplish more without simply adding more manual work as the business grows.

AI Is Becoming Part of the Core

This shift also explains why an insurer’s core platform strategy and AI strategy are becoming increasingly connected. An AI application can demonstrate impressive capabilities in isolation, but creating meaningful operational value requires connecting intelligence to the systems where insurance work actually happens.

For underwriting and claims, AI needs access to trusted core data and must operate within established workflows, business rules, security controls, and governance frameworks. Modern core platforms can provide that foundation, helping move AI from experimentation toward practical use within day-to-day insurance operations.

At BriteCore, we believe the future of insurance technology is not about bolting AI onto existing processes. It is about embedding intelligence into the core insurance platform and workflows insurers rely on every day, helping people work faster, make better-informed decisions, and focus their expertise where it creates the greatest value.

BriteCore’s 2026 survey suggests insurers are already moving in this direction. Underwriting and claims are simultaneously among the industry’s greatest opportunities for operational improvement and its most promising applications for Gen AI. That convergence points toward a new insurance productivity equation, one in which people, core workflows, and AI work together to help insurers accomplish more, respond faster, and scale more effectively.

The next chapter of insurance productivity will not come from automation alone. It will come from making intelligence an integral part of how insurance work gets done.