Data management

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.

When AI is simply layered on top of policy-centric platforms, batch-based processes, and siloed data models, it inherits their limitations.

Insurance companies need more reliable, bottom-up data and more strategic technology partnerships.

A collection of stories related to artificial intelligence and its impact on the insurance industry from 2025.

The most impactful data today is clean, structured, operational data collected across the entire policy lifecycle.

It's important that managing data enables speed, accountability, and trust at scale.

The adoption of AI requires buy-in from all departments and levels, and is a tool that can help insurers manage vast amounts of data more effectively.

Today's emerging technology trends have given way to a measured approach focused on compliance and sustainability.

INSTANDA CEO Tim Hardcastle discusses the risks and rewards of launching an insurtech.

A look at why causal reasoning—not more data—must drive insurance innovation.

INSTANDA CEO Tim Hardcastle shares some of the lessons he's learned from launching an insurance technology firm.

Carriers re-evaluating their company's business process outsourcing expect the integration of Agentic AI into workflows for greater efficiency.

When it comes to digitizing company processes, many mid-market insurers can scale smarter with automation and strategic partnerships.

Fraud detection and prevention have become key reasons for carriers to implement artificial intelligence.

Human cognition isn't software; it's a complex, adaptive system influenced by fatigue, stress, routine and ingrained biases.

Three principles for modernizing data infrastructure.