Data management

The enthusiasm around agentic AI in reserving isn't wrong but ahead of the infrastructure required.

Companies like MSI, AGI and VIPR are finding that the best way to benefit from AI is to keep a tight grip on the data that they feed into those tools.

Real improvement in managing uncertainty from a risk perspective won't come from better technology alone.

VIPR created an insurance native platform, built for insurance data: AI-enabled technology solutions for the delegated authority and program business insurance markets.

Only 24% of insurers consider themselves to have a leading edge on data management maturity.

Insurtechs have a major opportunity to address the industry's lack of data transparency, according to Ashwin Agarwal. "Whoever builds that trusted, transparent pricing layer first sets the terms for the entire industry."

The best place to start AI adoption is tasks where employees already describe them as repetitive, slow or unnecessarily difficult, writes Amy Carlisle, president of MSI.

Connected systems can help consumers understand each stage of the life insurance journey and ensure a more seamless, less fragmented consumer experience.

Legacy infrastructure, data challenges, workflow integration issues, regulatory concerns and skill shortages remain key obstacles in 2026

Travelers made a major bet on AI when it committed to developing its own in-house large language model, TravelersLLM. CTO Mojgan Lefebvre discusses how the company determines the technology's success.

Effective digitization eliminates manual data transcription while protecting the insurer's view of risk.

Instead of waiting for claims to confirm damage patterns, carriers can begin identifying likely impact zones earlier.

Can an insurer explain its decisions and demonstrate that AI is being used fairly and responsibly?

The next generation of pricing will harness AI, behavioral analytics and real-time data streams.

By reducing data sprawl, improving governance, and preparing for forensic investigations in advance, organizations can strengthen their security posture and ensure they are ready to meet the demands of insurers when it matters most.

Tech gives insurers a chance to price risks more accurately, make buying insurance faster and create new products and services.

The insurance industry doesn't have an AI adoption problem—it has a structural design problem.

It is not just about modernizing systems, but about standardizing how transactions are processed and how data is exchanged across the ecosystem.

The goal is to improve risk management and expand access to more customers in markets that better data now makes possible.

The market for such coverage could reach $10 billion in premiums in 2026, analysts led by Charles-Marie Delpuech and Patricia Kwan said in a note published Monday.