Summary
This guide outlines the seven principles for creating predictable and defensible return on investment (ROI) from artificial intelligence (AI) initiatives. It begins by addressing the current challenges faced by organizations, where accelerated AI investments have not consistently yielded measurable returns. The document highlights that a significant percentage of enterprise AI pilots fail to deliver profit and loss impact, leading to pressure on budgets and expectations from business units. The principles include establishing finance-grade business cases, ensuring visibility of costs, and implementing shared accountability among stakeholders. It emphasizes the importance of controlling usage economics, conducting sensitivity modeling, and tying governance triggers to ROI. The outcomes of following these principles are presented as predictable cost curves, enterprise adoption, and transparent value realization, ultimately positioning AI as a strategic asset rather than a speculative endeavor. The guide concludes by contrasting the scenarios of AI implementation with and without discipline.
