Your customers don't have a license. Neither do your prospects, your partners, your dealers, your applicants, your members or the technician on a shared tablet in your plant. Every one of those people has questions your business already knows the answers to, and not one of them can be served by an AI tool that requires an E5 seat to work.
That's not a flaw in Copilot—it was built to make licensed employees faster inside Microsoft applications and it does that well. But it means the AI use cases with the clearest revenue and deflection impact are, by design, on the other side of a wall: the support experience that answers customers at 2 a.m.; the portal that stops your channel team from fielding the same product question forty times a week; the AI you embed in the software you sell; the assistant that reaches into recorded expertise your longest-tenured people are about to take with them.
This session is about those use cases specifically—what they look like and can return, and why teams that try to build them one at a time stall out after the first. You'll see how a single governed knowledge layer serves all of them at once, with source-cited answers, measured retrieval quality and access controls that work as well for an anonymous website visitor as for an employee.
What You'll Learn
- What customer self-service that actually deflects tickets looks like: How to put cited, accurate answers in front of anonymous visitors on your public site, drawn from the same documentation your support team uses
- How to do partner and dealer enablement without headcount: Serving external users who will never enter your tenant, on content you already maintain
- When AI becomes a feature you ship: Embedding governed search and assistance directly into the software you sell, with the citations and audit trail your customers' compliance teams will ask about
- Why the fifth use case costs less than the first: How one indexed, governed layer serves every audience and every surface, instead of a separate pipeline per project
- How it works: The same knowledge layer answering a public visitor and an internal employee, with different permissions, visible citations and continuous quality scores on every answer