Insurance Industry on the Cusp of AI-Driven Transformation
The global insurance industry is bracing for significant changes as artificial intelligence (AI) continues to evolve and integrate into its business models. Industry experts predict that AI will not only transform the industry’s skill base but also revolutionize risk management and claims processes, making them more predictive and less reactive.
During a recent Financial Times webinar, Troy Dehmann, Beazley’s chief operating officer, emphasized that the biggest transformation the industry is undergoing is around skills. “When we talk about transformation, we could say lots of things around automation,” Dehmann said. “I think the biggest transformation that you’re going through is around skills.” Dehmann highlighted that every insurance role will be affected in some way by Agentic AI and Generative AI (GenAI) over the next five years.
Michael Föhner, Swiss Re’s global head of data and AI governance, echoed Dehmann’s sentiments, noting that the speed at which the industry needs to adapt is “rather frightening.” Föhner stressed the need to define and implement upskilling programs to manage AI-driven results effectively. He likened the use of AI to driving a fast car, saying, “You have to be upskilled to manage this fast machine.”
Mohammad Khan, partner and head of general insurance at PwC UK, predicted a cultural shift in the industry from reactive processing to continuous risk and claims management. “I think our culture will shift from being what I would call reactive processing to continuous risk and claims management,” Khan said. He believes Agentic AI will enable insurers to make more informed decisions and analyze future risks’ impact on current decisions.
Current AI Applications in Insurance
Föhner shared how Swiss Re is currently leveraging GenAI to process unstructured data efficiently. He mentioned that 80% of the data his firm needs to process is unstructured, and GenAI has been a “magic tool” in handling this data quickly. The firm has implemented an AI-powered underwriting assistant called Life Guide Scout, which allows underwriters to ask questions in natural language about underwriting certain risks.
Dehmann agreed, stating that Beazley is using GenAI for various tasks, including reading, summarizing, and extracting data for underwriting and claim submissions. He emphasized the importance of governance and guardrails in AI implementation, likening the relationship between underwriters and AI to “sparring partners” where AI is not allowed to operate independently.
Understanding Agentic AI
Khan provided a clear definition of Agentic AI, distinguishing it from GenAI. “I would define Generative AI as a class of artificial intelligence models capable of creating new content… by learning patterns from existing data,” he explained. In contrast, Agentic AI is a sub-class of GenAI that “possess agency” and can act independently, pursue goals, and make decisions.
As the insurance industry continues to embrace AI, the need for upskilling and reskilling becomes increasingly apparent. The integration of AI is expected to bring about more predictive risk management and customized insurance products, ultimately transforming the industry’s landscape.
