MCCM Wiki
Choosing the first AI workflow
Pick the first AI workflow where one owner already feels weekly pain, the inputs are available without a six-month data project, and a human can review the output in minutes. If any of those three is missing, choose a smaller job.
Teams often start with the flashiest demo. That creates excitement and no durable habit. MCCM starts with a process someone already owns.
Three filters that matter
- Frequency - the task happens often enough that time saved is visible in 6–10 weeks.
- Reviewability - a person can spot a bad output without a research project.
- Access - the needed files or systems are reachable under your privacy rules.
Good first candidates
Weekly reporting packs, inbox or ticket triage, first drafts of customer replies, meeting notes into action lists, and document sorting are common wins. They share a pattern: repetitive structure, clear “good enough” bar, and an owner who already does the work.
Bad first candidates
Skip jobs that need perfect legal language on day one, cross every system in the company, or have no human reviewer. Also skip “AI strategy” as a workflow. Strategy is an audit output, not the automation itself.
How to decide in one meeting
List five painful tasks. Score each on frequency, reviewability, and access (1–5). The highest total with a named owner becomes the pilot scope. Write the KPI before tools. Then shape a prompt workflow or light automation around that job.
What done looks like
Done means the owner runs the new path for two consecutive cycles without falling back to the old scramble, and the KPI moves in the agreed direction. Expand only after that.
Related
See From audit to pilot, AI pilot KPI examples, and AI pilot.