Most conversations about AI for project managers stop at personal productivity. Though useful, that's table stakes now, not where a project manager's leverage lies. The leverage is in how the team adopts AI: the governance, process, and context that turn individual experimentation into organizational capability.
Drawing on technology delivery programs in regulated financial infrastructure, this session works through the questions adoption actually raises. How do you enable AI under data sensitivity constraints? What happens to your team's skill profile – and does it move in the direction you'd expect? What does adoption actually do to the workload of your individual contributors? And when so much can be delegated to a model, what is the one thing a human still has to supply?