The Case for Specialist AI

Enterprise AI has moved past the question of whether to deploy an assistant — nearly everyone has one. The real work now is deciding what happens around it: what the assistant handles on its own, and what needs a specialist layer behind it for precision, control, and depth it can’t provide alone. That question is getting harder, not easier, as knowledge workers spread their day across chat interfaces, command lines, and MCP-connected tools rather than one dashboard. As assistants absorb more of that daily work, every company faces a second, related choice: what deserves to live in its own dedicated environment, and what should be embedded directly into the flow of work. The mature answer isn’t “everything becomes embedded” — it’s a considered duality, often both, depending on the task, the user, and the stakes. This session explores how business leaders are making that call in practice.