Use Cases for AI in the Insurance Industry: Claims, Customer Service & more
Reuters Events Insurance
Thought leadership and industry analysis to help network, discuss, learn and shape the future of the insurance industry.
With investment sentiment for AI within the insurance sector growing, it is important to understand where insurance organizations expect to utilize the technology, why such investments are being prioritized and how the success of any investment will be measured.
As the below chart indicates, claims was the most-mentioned function or division focusing on implementing generative AI today, followed by customer service.
The correct usage of AI can help insurance carriers understand and respond to customer needs, provide personalized services, and optimize overall customer satisfaction. However, the road to progress is paved with challenges; regulation, employee buy-in, data structuring and more stand in the way of harnessing the full power of AI.
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Assessing the objectives for investing in AI more holistically, the most commonly cited driver for AI investments is to increase operational capacity or volume of business, selected by more than one quarter (26%) of respondents. The second most common driver was to reduce operational costs (17%), followed by improving external customer experiences and targeting new customer groups, cited by 14% of respondents each.
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The success of investments in AI is largely being measured by an organization’s profitability or productivity following an investment. Those two measures were selected by 33% and 22% respectively, indicating that organizations are expecting investments in AI to have a direct impact on their bottom line.
Our research therefore indicates that investments in AI are being made for targeted improvements in the profitability and efficiency of specific departments within insurers, namely claims and underwriting. This contrasts with other technologies profiled within our research, such as digital portals or CRM systems, which have more holistic aims and intended outcomes.
Insurers looking to increase the efficiency of their claims and underwriting processes can therefore realistically look to AI tools and technologies as a viable option. There must be careful consideration afforded to other factors before making such an investment, however, with implementation and budget key to success.
There is, however, an expectations that new use cases for AI will emerge as experience with the technology grows. Wendy Crosley , Global Director of Underwriting Automation & Transformation at WTW says:
"While the initial use cases of AI in claims, customer service, and process automation mark significant strides, the revolutionary transformations in the insurance industry await early adopters. Beyond the basics, these pioneers have the opportunity to explore groundbreaking applications—predicting customer behaviors, offering tailored recommendations to underwriters, and leveraging diverse data sources for strategic decision-making. The door to innovative use cases swings open for those ready to embrace AI's full spectrum of possibilities."
Interested in more facts & figures surrounding Insurance AI investments? We asked 700+ insurance companies where they are investing in AI, what the key blockers are, and how successful it’s been – so you can benchmark your strategy against insurance-specific examples.