As insurers contend with challenges such as inefficient processes, inconsistent decision-making, and the underutilisation of data locked in unstructured documents, GenAI presents a transformative opportunity for underwriting operations. This is especially relevant in commercial lines and reinsurance, where the complexity of risks has traditionally resisted standardisation. The significant volume of unstructured data in these areas still demands a heavily human-driven underwriting approach, making GenAI an ideal solution to revolutionise this process.

Generative AI is revolutionising how insurers extract and utilise unstructured data, with large language models outperforming traditional solutions without requiring extensive training. This technological advancement enables more efficient business operations whilst laying the foundation for broader AI implementation in insurance, though evaluating the growing number of vendor solutions remains challenging.

Generative AI (GenAI) promises major benefits across industries. While insurers and others have quickly adopted GenAI tools or started proof-of-concepts, their true value is uncertain. This article examines GenAI's functionality, potential insurance applications, and steps for effective integration into existing processes.

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