New research by IBM’s Institute for Business Value identifies a disconnect between how insurers and their customers prioritise the use of generative AI (GenAI), with industry executives focusing on experience while their clients are seeking personalized risk products and insights.
Findings from a survey of 1 000 insurance C-suite executives in 23 countries and 4 700 insurance customers in nine countries are outlined in “Generative AI in the Insurance Industry: You Can’t Win if You Don’t Play”.
“The insurance industry has made headway in generative AI with customer experience and chatbot enhancements, but insurers must focus on adopting comprehensive governance frameworks that ensure transparency, privacy, and explainability to ensure they are building trusted AI assistants and reliable processes,” says Mark McLaughlin, director of global insurance with IBM Technology. “There are also significant opportunities in connecting customers to the right products.
“Leveraging AI across the enterprise will be critical to improve both customer risk experiences and to implement the underlying IT tools that power those experiences.”
Key takeaways from the study include:
- Insurance CEOs surveyed were almost evenly divided on whether they see generative as more of a risk (49%) versus an opportunity (51%).
- 77% of industry leaders who responded acknowledge that GenAI is necessary to keep pace with competitors.
- Investments in gen AI are expected to surge by over 300% from 2023 to 2025 as organisations move from pilots in one or two areas to implementations in multiple functions across business lines.
- Only 29% of insurance customers queried said they are comfortable with gen AI virtual agents providing service, with only 26% saying they trust in the reliability and accuracy of advice given by generative AI
- Organisations choosing less-centralized operating models to develop gen AI capabilities can improve business outcomes by up to 14%
The IBV outlines the following recommendations:
- Build more tailored products with flexibility, advice, and linkage to risk data
- Match those products intelligently to customers’ needs
- Address trust issues with strongly ethical, governed AI
- Also use AI to connect the underlying risk data and address long-standing insurer and financial service provider technical debt
- Deploy – and govern – AI across the enterprise with local knowledge experts empowered to connect AI to the insurance value chain