One common use case I'm finding in Public Sector procurement is, I believe, pretty common to procurement processes everywhere — and that's drafting an RFQ (Request for Quote) document. For vendors, it's writing RFQ responses that's the big use case.
RFQs can be long, complex documents and building them out so you don't miss any relevant points can be hard for procurement teams when they're on a new project. Using AI to gather questions/items from prior RFQs can be time consuming and complicated — but AI helps get started by reading all the earlier versions and drafting a new comprehensive version. It's not always perfect, but it can get you 90% of the way there and save hours of effort.
If you're responding to RFQs, this hours-long or days-long process can take a few minutes with AI. If you've got a library of prior responses, AI can quickly read them and compile them into a response, saving a lot of time. The one issue I've seen reported is that the formatting of RFQ responses can be challenging for an AI to emulate — and as a vendor you HAVE to get that right. But using AI can turn even the most complicated RFQ format into a much simpler cut-and-paste formatting issue, and not a 2-day research project!
