‘Over the next three years we will see a dramatic expansion into underwriting processes, pricing and customer-facing areas,’ says business architect
While artificial intelligence (AI) has become common in the insurance industry, most notably in claims handling, many firms are beginning to turn their attention to developing the technology in more mature and nuanced business areas.

This is according to a new report from Sollers Consultancy titled Beneath the Surface of AI in Insurance, which highlighted underwriting, prevention and sales as the next key areas for AI implementation.
Optimism around the role of AI in insurance can be traced to the rapid uptake of large language models (LLM) among firms, with some 82% of respondents in a supporting survey reporting using them in the workplace.
However, the report suggested that developments in IT architecture would be needed to enable more meaningful and efficiency-driving use cases of the tooling.
Indeed, only 30% of surveyed firms reported that they had implemented or were in the process of implementing AI workflows in their underwriting departments and only 15% said they were using or planned to use the tool for analysing contracts.
Falling behind
Piotr Kondratowicz, business architect at Sollers, said: “Insurers that fail to establish governance structures to support AI transformation risk falling behind in a market that is rapidly moving towards AI, automation and predictive decision-making.
Read: Davies AI leader urges stakeholders to not fear ‘failing fast’ and fuel AI claims innovation
Read: Brokers are ‘logical latecomers’ to AI use as ‘old guard’ believe in certain way of doing tasks
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“AI is primarily used to automate data capture, document processing and parts of the claims handling process.
“Over the next three years, however, we will see a dramatic expansion into underwriting processes, pricing and customer-facing areas such as product offerings and digital services.”

He graduated in 2017 from the University of Manchester with a degree in Geology. He spent the first part of his career working in consulting and tech, spending time at Citibank as a data analyst, before working as an analytics engineer with clients in the retail, technology, manufacturing and financial services sectors.View full Profile
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