Direct answer
A business is ready for AI when it has a valuable repeatable use case, controlled data permissions, approved tools, clear human-review requirements and a way to measure results. Buying licences before those foundations are in place often magnifies existing information and governance problems.
Start with a workflow, not a product
Look for repetitive work involving summarization, drafting, classification, internal search or structured follow-up. Define the current time, error rate or delay before testing AI.
Check data permissions first
AI tools can surface information a user is already allowed to access. Overly broad SharePoint, Teams or file permissions therefore become a readiness problem.
Pilot with measurable boundaries
Select a small group, approved data and one or two workflows. Measure quality and time saved, require human review and record issues before expanding.
Frequently asked questions
Is public generative AI safe for confidential work?
Do not assume so. Review the specific service terms, account type, data handling, retention and administrative controls before entering confidential information.
What should an AI acceptable-use policy cover?
It should identify approved tools, prohibited data, review requirements, intellectual-property considerations, accountability and the process for requesting a new use case.
Primary reference: Statistics Canada — AI use by Canadian businesses ↗