AI can radically speed up coverage decisions – but if you get the foundations wrong, you amplify risk instead of reducing it. In this on‑demand video, Bernie Camus, Head of AI at Sprout.ai, shares five practical rules insurers must nail before they lean on AI for policy coverage decisions that affect customers, compliance, and loss ratios.
Sprout.ai’s policy coverage checking is purpose‑built and intensively trained for insurance – not adapted from a generic LLM. In under 3 minutes, Bernie explains where things most often go wrong in real deployments, and reveals his top tips for AI that is fast, consistent, and auditable from day one.
You’ll learn how to:
• Build AI on top of real coverage decisions, not just documents or synthetic data.
• Treat extraction as a coverage logic problem so clause relationships don’t break.
• Design evaluation that reflects messy, real‑world claims – not just happy paths.
• Fix problems in the core architecture instead of piling on brittle rules.
• Make every AI decision explainable, traceable, and defensible.
If you’re asking “Can I rely on AI for real policy coverage decisions?” rather than “Does AI work?”, this session is designed for you.
Watch now and benchmark your approach against what leading insurers are doing today.