What this means in practice

  • Ask teams openly rather than monitoring them covertly.
  • Check what data goes into each tool and the vendor’s data-use terms.
  • Approve, restrict or retire each tool with a recorded reason.
  • Update the AI policy and tell people what changed.

How Lid Vizion approaches it

We start with the business decision and operating context, define ownership and measurable milestones, then use configuration, integrations, automation, or custom software only where each earns its place.

See it as a workflow

  • Quarterly AI usage and risk review: Each quarter, take stock of which AI tools people actually use, what data goes into them and how that matches policy, so leadership can approve, restrict or retire tools with evidence instead of guesswork.