Business & money
AI Adoption Readiness Score
Seven questions about ownership, data and process — the things that actually decide whether an AI rollout survives its first quarter.
Pilots without an owner quietly die after the demo.
Retrieval quality is decided by your filing, not your model.
You cannot automate a process nobody can describe.
Adoption, not licences, decides the return.
Without rules, staff use AI anyway — just invisibly.
Free tiers stall exactly when a pilot starts working.
Unmeasured savings get argued away at the first budget review.
Readiness
50/100 · Early
There is appetite but not yet foundation. Fix the gaps below before buying anything else.
Do this next
Document your most repeated workflow and assign an owner.
Why most AI pilots stall
Failed rollouts almost never fail on model quality. They fail because nobody owned the outcome, the data the tool needed was spread across four systems, or the workflow being automated only existed in one person's head. None of those problems is solved by a better subscription.
The businesses that get returns start narrow: one documented workflow, one accountable owner, one baseline metric captured before anything changed. That is unglamorous, and it is the whole difference between a pilot that scales and a demo everyone remembers fondly.