What readiness actually means
Readiness isn't a clean data warehouse. It's enough operating clarity that an AI tool plugged into your workflow improves it instead of accelerating the mess underneath.
Workflow clarity
- Can you draw your top three workflows on one page each?
- Does each step have a single accountable owner?
- Are the triggers and outputs explicit?
Data visibility
- Do you know which system is the source of truth for each entity (customer, deal, project)?
- Can a frontline operator find a record in under 30 seconds?
- Are at least the top fields consistent across systems?
Ownership
- Is there a named owner for the workflow, not just the people doing the work?
- Does that owner have the authority to change the workflow?
Tool integration
- Do core tools talk to each other or only via copy-paste?
- Is there at least one place where the full picture comes together?
Risk and governance
- Do you know which workflows touch sensitive data?
- Is there a baseline policy for AI tool use among employees?
- Are external-facing outputs reviewed before they go out?
Decision accountability
- Are the top recurring decisions documented (who decides, what input, what record)?
- Is there a habit of writing down the rationale, even briefly?
Minimum viable readiness
You do not need yes to every line. You need enough yeses on workflow clarity and ownership that AI lands in a known place with a known owner. Everything else can be improved alongside the first project, not before it.
What to fix first
The single highest-leverage fix is usually naming an accountable owner for each major workflow. Almost every AI failure traces back to "no one owned the change."