How can enabling functions lead enterprise AI transformation instead of just supporting it?

In this podcast, Kayleigh Lowes, Transformation Manager for Thomson Reuters' AI adoption strategy, speaks with Natalie Runyon, Content Strategist for the Human Side of AI at the Thomson Reuters Institute, and explains that these in-house functions can shape how AI changes everyday work within an organization.

Lowes argues that treating the review of AI output as a deliberate, recognized part of the work is a key outcome of these efforts and that a draft is not finished when it's created by AI, but rather when a person checks it. She also explains that the real measure of success is process change — not how many people sign in to work with the AI tools.

Why you should listen:

1. Learn to lead AI transformation instead of just supporting it — Supporting AI transformation means providing licenses, training, and communications, while leading it means building the judgment people need to decide how AI should change their work.
2. ‍Make review and verification visible — Too often, review is overlooked. A draft is not finished just because AI produced it, and the person checking it is usually the last safeguard before it reaches someone else, so that checking should be made visible.
3. Find best ways to measure AI transformation success — They should measure how processes change, not how many employees sign in to AI tools, because login counts show access but not whether work has improved.

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