Data and AI projects rarely fail on technology. They fail on data trust, semantics, context, and culture - the parts that get skipped in the slide-deck version. Join Marie Fenner from Piano for an open roundtable on the common ingredients behind the projects that make it through: success defined in revenue or efficiency terms rather than model metrics, data people are willing to act on, shared semantics and rich context so answers mean the same thing across teams, and a culture that keeps the work moving once the pilot ends. We'll also look at projects that started small and delivered outsized business results.

Bring a question, or a war story. Ideal for data and analytics leaders, data governance leaders, and AI project leads -  anyone who owns data, analytics, or AI outcome.