Many organizations begin AI governance by drafting policy language or debating future controls. Those are useful steps, but they are rarely the best first step. The better starting point is to identify which tools are already in use, where they are being used, and what kinds of information are moving through them.

Without that inventory, leadership is often making decisions with only a partial view of risk. Teams may already be using workplace AI to summarize meetings, generate client-facing drafts, review contracts, or support internal analysis. Each use case has different implications for privacy, security, oversight, and acceptable use.

What to inventory first

  • Approved and unapproved AI tools currently in use
  • Business teams or roles using those tools
  • Data types entered into prompts or uploaded to the platform
  • Outputs being used internally versus shared externally
  • Who is accountable for reviewing use cases and exceptions

This does not need to become a large documentation exercise. A simple inventory built with clear ownership can quickly surface which use cases are low-risk, which need better controls, and which should pause until expectations are clearer.

For Canadian businesses, this also helps create a stronger bridge between AI use and broader governance expectations. Once leadership understands the current state, it becomes much easier to build acceptable use guidance, assess data handling, and prioritize the next set of controls in a practical way.