To consider the prospects and potential for generative artificial intelligence in 2024 and beyond, the key may be to follow the money.
Insurance industry professionals and experts expect carriers will spend more on Gen AI in the new year and that use of the technology will grow in the industry.
This year, carriers were still considering use cases for Gen AI, according to Rima Safari, a partner in the insurance practice at PwC. Soon, she said, they will set priorities for where and how to use Gen AI and then begin implementation. "Many of them did not have funding allocated to it for this year," she said. "But they're certainly counting for large investments associated with this for next year."
The next 12 to 18 months may see a lot of activity, but if using Gen AI takes hold, it will likely take longer to be prevalent, according to Andy Logani, chief digital officer at EXL, an insurtech management consulting company. "It's more back loaded over two to four years, than 12 to 18 months," he said.
Overall, insurers should think long term about how they may apply Gen AI to customer interactions and creating value, according to Jared Vestal, vice president of growth and journey marketing at Geico. "Insurance is a high cost and low growth business," he said. "You really want to be thinking ahead three years, five years, nine years in the future, and how are you changing that future further out."
Technology professionals in all fields are becoming more comfortable with AI and open to engaging with it, according to a survey of 2,000 people conducted by MetLife in August and presented at its Triangle Tech X conference in October. Fifty-eight percent of employees surveyed said they were willing to engage with AI and 51% said they would be interested in learning to develop new tools and technologies. Only 15% of respondents said they were not willing to engage with AI, mostly because they feel unprepared.
Gen AI potentially could address insurance professionals' unease with the technology. Large language models have potential to orchestrate communication within organizations such as insurance carriers, as Joseph Ours, AI strategy and director, modern software development at Centric Consulting, explained.
"Right now, largely linear models have the ability to understand a structured API call, extract information from a conversation, fill out that API call, execute it and get results back to use or act upon," he said. "You can do that between systems. You can do that between humans and systems."
One of the biggest potential insurance uses for Gen AI is in customer service communication, particularly for hyper-personalization of interactions. When a customer calls their insurer, EXL's Logani said, hyper-personalized Gen AI can provide every piece of information available about that customer, and tell the customer what product they have – and whether the customer could take an additional annuity with their insurance. "It's using that call and changing it to customer advice, through hyper-personalization," Logani said.
Gen AI has the potential to improve communication with insurance customers by improving the transparency about coverage decisions, according to Ted Epps, life technology and group alliance leader at EY. "Gen AI will tell you why somebody was approved or declined for a particular [life insurance] policy, and that's one of the things that regulators have an issue with -- the black box about understanding why a decision was made," he said. "A Gen AI model could come back and say we approve at a preferred rate or select rate, because this person has a good BMI, is a nonsmoker and in good health based off these factors. That's a different model than what a regulator usually gets."
Within the mechanics of underwriting, Gen AI can build on what predictive models do, according to Tyler Jones, chief marketing officer at Clara Analytics, a P&C claims AI technology provider.
"We're solving problems using the predictive models plus the Gen AI technology to have advanced explainability user experiences," he said. "Where we're going is much beyond just the predictive and generative piece of things, to more of a prescriptive environment, where you're providing the right actions to take with justification, with those probabilistic outcomes."
Gen AI brings a stronger real-time capability to data management, as Adrian McKnight, chief digital officer of WNS, a business process management company, explained. "The ability now for real-time data to be utilized in a real-time sense, analyzed and synthesized by generative AI is really significant," he said. "With underwriting and pricing, Gen AI helps gather enormous amounts of data for decisions and analyze that data, look for patterns, anomalies and consistencies across the data and summarize it."
