From Bottleneck to Bottlenectar: How AI and Process Mining Unlock Hidden Efficiencies
TL;DR for operators A recent case study from If P&C Insurance is useful because it does something most AI automation stories conveniently skip: it follows the work after the model is deployed.1 The company used an LLM to identify specialised claim parts in insurance claims, a task that had depended on human claim handlers and specialist knowledge. In offline evaluation, the fifth model iteration built around GPT-4o-0806 reached 81% recall in English, above the company’s 70% human baseline. That sounds like the usual “AI beats humans” headline. Mercifully, the paper is more interesting than that. ...