This source uses the metaphor of an AI graveyard to describe the high failure rate of corporate machine learning initiatives that lack a clear purpose. To avoid this outcome, the author suggests prioritizing concrete business problems over technical novelty and establishing measurable success metrics from the start. Success also requires securing stakeholder buy-in by communicating value in terms of financial and operational impact rather than technical jargon. Furthermore, teams must treat production deployment and long-term monitoring as fundamental requirements rather than secondary concerns. By focusing on scalability and integration, organizations can move beyond simple demonstrations to create tools that offer lasting enterprise value.