Introduction to AI in Insurance
Artificial intelligence has been part of the insurance sector for years, with the Finance function in many businesses being the first to automate. However, what’s remarkable about AI in this sector is how directly the technology is woven into day-to-day operational work. AI is used in areas where insurers spend most of their time and money, such as claims handling, underwriting, and running complex programs.
Industry Giants Leading the Way
Industry giants like Allianz, Zurich, and Aviva have published evidence in the last 12 months illustrating their shifts from experimentation stages to production-grade tools that support frontline workers in real workflows. These companies have made significant strides in implementing AI in their operations, resulting in improved efficiency and reduced costs.
Simple Claims: Fewer Admin Bottlenecks
Claims operations are a natural proving ground for AI because they involve a combination of paperwork and human judgment, often undertaken in an environment of time pressure. Allianz’s Insurance Copilot is an AI-powered tool that helps claims handlers automate repetitive tasks and gather relevant information that would otherwise require multiple searches on different systems. The tool starts with data gathering, summarizing claim and contract details, and then performs document analysis, flagging discrepancies and suggesting next steps.
Complex Documents to Usable Decisions
The quality of underwriting is determined by the quality of information available. Aviva uses the example of underwriters needing to read GP medical reports, which can sometimes amount to dozens of pages of medical text. The company is launching an AI-powered summarization tool that uses genAI to analyze and summarize these reports, allowing underwriters to make faster, more informed decisions. The AI functions let underwriters review summaries and make the final decision, with the technology reducing the time spent reading and increasing processing speed.
Uncertain Contracts and Servicing in Multinational Programs
Commercial insurance is an area with its own challenges, including complexity from working in multiple jurisdictions and regional differences between policies and stakeholders. Zurich says generative AI’s ability to process unstructured information lets multinational insurance work more easily across several countries, helping build quicker, more accurate pictures of commercial insurance offerings and simplifying submissions in different countries. The company also highlights contract certainty as a practical outcome, with GenAI helping internal experts compare, summarize, and verify coverage in a program using the operator’s native language.
The Common Thread: Augmentation, Not Automation-for-Automation’s Sake
Across these examples, a consistent pattern emerges: AI handles the heavy lifting of reading, searching, and drafting, while humans remain accountable for consequent decisions. Operational control and scalability are treated as major concerns, with pilots, testing, domain-by-domain tuning, and expansion into lines of business being integral to the narrative.
What This Means for the Sector
Insurers see faster cycle times, better consistency, reduced manual work, and a path to scaling. Their challenge is implementing tools responsibly, which is defined by secure data handling, explainability where needed, and the training of teams to question outputs appropriately. AI is becoming less of a headline in the sector and more of an everyday reality, a practical silicon colleague in the routine work of insurance profitability.
Conclusion
The use of AI in the insurance sector is becoming increasingly prevalent, with industry giants leading the way in implementing production-grade tools to support frontline workers. The technology is being used to improve efficiency, reduce costs, and enhance decision-making. As the sector continues to evolve, it’s likely that AI will play an even more significant role in shaping the future of insurance.
FAQs
- Q: What is the main benefit of using AI in insurance claims handling?
A: The main benefit is the reduction of admin bottlenecks and the ability to automate repetitive tasks, allowing claims handlers to focus on more complex tasks. - Q: How is AI being used in underwriting?
A: AI is being used to analyze and summarize complex documents, such as medical reports, to help underwriters make faster and more informed decisions. - Q: What is the challenge of implementing AI in the insurance sector?
A: The challenge is implementing tools responsibly, which includes secure data handling, explainability, and the training of teams to question outputs appropriately. - Q: What is the future of AI in the insurance sector?
A: AI is likely to play an even more significant role in shaping the future of insurance, with the technology becoming an everyday reality in the routine work of insurance profitability.
