Gen AI is moving from potential to reality for insurers

The first in a series on how the insurance industry now sees Gen AI and its potential.

Last fall, the insurance industry was looking at how to use Gen AI after the technology took a lot of hype.

This fall, the industry moved toward Gen AI-specific applications such as operational securityrisk management, underwriting, claims and applications for small and medium-sized businesses.

Industry spending on Gen AI capabilities is increasing and more insurers are adopting the technology, according to consultant research.

Redhand Advisors’ June survey of 998 risk management information systems (RMIS) professionals found that one in ten are now using Gen AI, but nearly half of those surveyed expect to adopt Gen AI in the next three years.

In July, Boston Consulting Group research highlighted the projected growth of Gen AI for insurers. A survey of 330 IT buyers at the director level or above, across various industries, found that their investment in Gen AI will increase by an average of 30% over the next three years. The research also highlighted industry adoption and plans and found that insurance is an industry behind, with at least 40% of its companies having little or no adoption of Gen AI.

If insurance companies are as interested as these surveys indicate, there seems to be plenty of room for them to ramp up their use of Gen AI.

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Rima Safari, partner in PWC’s insurance practice, said commercial lines show the potential for Gen AI applications. “When broker requests come in, we see a lot of value in ingesting data before we go into the underwriting process,” she said. “We see the same thing in group insurance, as opposed to personal lines, where there’s a lot of data to ingest.”

Jason Ralph, partner at McKinsey & Co., speaking at the National Association of Insurance Commissioners (NAIC) summer conference on August 13, identified four ways Gen AI can create value for insurance companies:

• Enabling customer journeys. This is about applying Gen AI in the form of a chatbot to support customer service representatives.
• Summarizing complex information, to generate insights and create reports using otherwise untapped data sets.
• Providing context. Creating new marketing materials, going beyond just digesting and responding to information.
• Development of technologies. Using Gen AI to digest text and code and also digest what code is doing in insurers operations. This can reduce legacy systems upgrades that typically take five years to less than two years to complete.

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However, Ralph warned, both the technology itself and the talent and data management capabilities may limit what insurers can achieve using Gen AI.

“We’ve seen a recalibration of expectations,” he said. “When we started talking to our customers about generative AI, it was mostly about finding use cases where the sky is the limit. Something that fundamentally transforms the way we do business and has unlimited potential. The ability to fundamentally change the way insurance is bought and sold We began to see very quickly that there were clear limits.”