A Systematic Approach to Experimenting with Gen AI
Organizations should approach gen AI adoption through structured experimentation and learning frameworks rather than ad-hoc pilot proliferation.
Summary
The article proposes a systematic methodology for evaluating and scaling gen AI capabilities across organizations. Framework addresses evaluation criteria, scaling readiness, and governance for responsible AI experimentation.
Editor's opinion
This piece makes a compelling case for treating AI adoption as a portfolio of structured experiments rather than a binary bet, which is exactly the right framing given how much uncertainty surrounds real-world AI impact. The Siemens shop-floor example is particularly valuable — showing how experimentation works in physical production environments, not just software — and the distinction between proper organizational experiments and the informal pilots most companies actually run is a point more leaders need to hear. A useful antidote to the "just deploy it" pressure many organizations face right now.
Key concepts
AI for Strategy · Digital transformation · Innovation management · Organizational learning