AI is gaining traction across the insurance industry, with businesses exploring its potential to reshape everything from underwriting and pricing to claims management. However, turning that interest into practical applications is proving challenging, as insurers grapple with the technology, data and infrastructure needed to make it work.

Fragmented data, ageing systems and disconnected workflows are among the issues standing in the way. There are also questions around cybersecurity, accountability and how much of the existing insurance infrastructure needs to change before AI can be used effectively.

FinTech Global spoke to Melanie Hayes, co-founder of KYND, Matt Twist, vice president of sales, EMEA, at Earnix, and Dan Simmons, CEO of Quensus, to understand what is slowing adoption and what insurers need to address before taking the technology further.

There is no single answer to how insurers should introduce AI. Some may choose to test new applications alongside existing systems, while others will look to incorporate them directly into their core technology. Much depends on the organisation, its existing infrastructure and the decisions it wants the technology to support.

For Hayes, however, the rush to adopt AI could mean insurers overlook some of the more basic security questions.

She explained, “What we do see, looking at a great many organisations from the outside, is that everyone is racing to get ahead of AI adoption, or at least to catch up with it. In that rush, the basic cyber hygiene that should sit underneath it is easy to miss.”

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