Agile organizations pride themselves on fast feedback loops, yet AI adoption decisions are routinely made with no feedback loop at all on their environmental and community cost. Every model an organization deploys draws on physical infrastructure: data centers, power generation, water, and land. Those costs concentrate somewhere, and too often they concentrate on communities with the least power to object. This session examines the documented case of data center expansion intersecting with under permitted power generation near a majority Black community, and asks what responsible adoption looks like when the true cost of intelligence is visible. Attendees will learn to separate verified findings from public narrative and apply a practical screening framework for evaluating AI vendor and infrastructure decisions against sustainability and equity standards before adoption, not after harm reaches families. This is responsible AI as an agile discipline: shortening the feedback loop between the decisions we make in sprint planning and the consequences they create in the physical world.