Insurers risk missing out on the commercial benefits of artificial intelligence as disconnected teams, legacy systems and isolated AI projects prevent them from turning data into faster business decisions, according to Earnix.

In a recent video interview, Earnix global chief marketing and communications officer Kathy Klingler discussed why improving insurance agility requires more than investing in new technology. She outlined how the company’s AIOS platform aims to connect intelligence across insurance operations and help providers translate insights into measurable business outcomes.

For insurers, the challenge is not simply a lack of data or analytical tools. Pricing, underwriting and customer-facing teams can operate separately, with limited access to shared information and insights. These organisational divisions can make it harder to respond consistently to changing market conditions and evolving customer expectations.

The growing adoption of AI has added another layer of complexity. While insurers are experimenting with the technology across different functions, initiatives can remain confined to individual departments or pilot projects, limiting their impact across the wider business.

Klingler argues that overcoming these barriers requires insurers to connect decisions throughout the insurance lifecycle while maintaining the controls and confidence needed in a regulated industry.

Earnix AIOS builds on more than 25 years of the company’s experience in intelligent decisioning, bringing capabilities across pricing, rating, underwriting and customer engagement into a connected environment. Rather than requiring insurers to replace their existing core systems, the platform is designed to work alongside established technology, linking data, models, applications and intelligence across business functions.

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