Making the AI Vision Real: Adapting Your Operating Model to Scale AI

You’ve declared your ambition to integrate AI into your function. You’ve approved a budget. A few use cases have launched. And yet the question that should have come first has no clear answer: what AI is actually for in this business. 

You’re not alone. Across the enterprises we work with, the pattern is consistent: the pressure to move on AI is real, the investment is approved, and the foundational work of defining purpose, aligning leadership, and designing the operating model gets treated as something to retrofit later. The pilots run, the tools get adopted in pockets, and a year on, the boardroom keeps asking what they’re actually getting from all of it. 

This is the session for leaders building AI from the foundation up, not retrofitting a solution across your organization. Drawing on our experience helping enterprises build the foundation for AI before scaling it, we’ll share what we’ve seen that separates the organizations getting this right from those running expensive experiments. It comes down to three moves: deciding what AI is for, aligning leadership behind it, and designing the operating model to deliver on it.