George Robbins of Shift Technology argues that the biggest AI mistake insurers can make is automating processes before checking that they are fit for purpose. AI is not a repair kit for broken workflows: applied to a fragmented or inconsistent claims process, it simply makes the same weaknesses move faster. In insurance, speed alone creates no value, and a faster bad decision is still a bad decision. The real question is not whether AI can do a task, but whether it should, and what still needs human judgement.
The best uses of AI are often the least flashy. They support experienced claims handlers, fraud investigators and underwriters by triaging information, surfacing missing documents, flagging inconsistencies and suggesting next best actions. The machine handles repetitive checks, while people focus on exceptions, nuance and decisions that affect customers. Governance matters just as much: in a regulated, trust-based sector, systems must know when to stop and hand over to a person, with clear escalation paths and accountability. Many AI projects fail because they start with the technology rather than the process, its purpose and what a good outcome looks like for the policyholder. Applied carefully, AI improves consistency and responsiveness; applied carelessly, it scales inefficiency and erodes trust.
Read the full article on Insurance Times to discover why insurers should make sure a process deserves to be automated before asking AI to do more.