Plain-language explanation
AI readiness means your team can say, in plain language, which workflows AI is allowed in, which data it can see, who reviews its output, and how you measure whether it helped.
Why it matters
Without readiness, AI ships mistakes as your mistakes, leaks data you intended to keep private, and gets measured by activity instead of outcomes.
Common questions
- Where should we start?
- What should never be sent to an AI tool?
- Who is responsible for reviewing AI output?
- How do we know it is actually working?