Map It Before You Automate It: What to Automate, What to Protect

Most AI adoption starts backwards — with a tool, not a problem, and with whoever's workflow is easiest to document. This hands-on workshop teaches a mapping method for diagramming attendees' actual end-to-end workflow and pinpointing where real friction lives, then adds a second pass most teams skip: asking whose expertise doesn't show up on that map at all.

Informal knowledge, workarounds, and judgment calls are often invisible in process documentation — and they're exactly what gets flattened when a team rushes to "AI-enable" a workflow. Attendees will map a real process from their own work, distinguish friction worth automating from friction that's actually load-bearing expertise, and leave with a short evaluation framework for building AI use cases that support judgment instead of erasing it. Grounded in sociological methods for studying how people actually work — not how org charts or process docs say they work — this session is for anyone who wants to adopt AI deliberately instead of reflexively.