Turning Data into Learning with Lightweight Experiments

What if your data could actually teach your organization something? In this episode of The Fault Line, Kim Scribner sits down with Melissa Reeve to explore how AI is reshaping experimentation from simple A and B tests to continuous testing at scale. They discuss how to build lightweight learning loops, avoid common shortcuts, and use AI as a thought partner to generate hypotheses, analyze results, and uncover root causes. The conversation focuses on moving beyond efficiency to drive real effectiveness, helping teams learn faster, think deeper, and build more adaptive ways of working.