AI and ML projects promise transformative value, but too often, they fall short of ROI expectations or create long lasting damage to a company's reputation. In this session, we’ll unpack the real risks behind AI initiatives, from data quality gaps and unclear success criteria to governance blind spots and a complete disconnect from business priorities. Through real-world examples of where things go wrong, we’ll identify the patterns that derail ROI and trust. You’ll learn practical strategies for scoping, communication, and stakeholder alignment to help clients and teams navigate the path toward sustainable, business-driven AI outcomes without succumbing to the hype cycle noise.