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The back office of an insurance company, he argued, is a prime example: binding a new policy or processing a small business loan currently requires multiple customer interactions, a front-line rep capturing information, a back-office team making a decision, and then a rep communicating that decision back. “These processes generally require either very long conversations or multiple interactions,” Buesing said, offering the examples of a front-facing representative capturing information while a back-office team works on the decision. “AI can perform those functions faster, run a customer history profile in real time while the customer is still speaking to the front-line rep, and help that human make a decision.”
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