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Applied AIManager5 hrsIn person / Live online

Measuring AI Adoption and Value

Licence counts and login stats say nothing about whether work has changed. This course builds a measurement approach you can defend: a baseline, a small set of honest metrics, and a report your leadership will trust.

What participants can do afterwards

  • Set a baseline before the next initiative rather than after it
  • Choose the few metrics that show changed work, not just logins
  • Separate time saved from value captured, and report both honestly
  • Present adoption to leadership without vanity numbers

Modules

4 modules, 5 facilitated hours.

  1. 1.What a baseline looks like

    1.5 hrs

    Measuring the work as it is now, before the next initiative makes the comparison impossible.

    • Capture a defensible baseline

  2. 2.Metrics that mean something

    1.5 hrs

    A small set of measures that show changed work, chosen against the vanity alternatives.

    • Choose metrics that show changed work

  3. 3.Time saved is not value captured

    1 hrs

    What happens to a saved hour, and how to report the difference honestly.

    • Report time saved and value captured as different things

  4. 4.Reporting up

    1 hrs

    The one-page adoption report a board will trust, built from the session's own numbers.

    • Build the adoption report your leadership will trust

How it is delivered

A facilitator runs the course live, in person or live online. Attendance is taken per session, participants submit work against the modules above, and a facilitator grades it. Those records stay with the organisation and can be exported.

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