AI success is no longer determined by model complexity alone. In modern enterprise settings, the effectiveness of AI initiatives fundamentally depends on the quality, governance, and relevance of the data driving those models. This article introduces a data-centric framework comprising three essential pillars: Good Data, Governed Data, and the Right Data. These pillars serve as foundational components that determine the scalability, integrity, and value of AI solutions. Drawing on industry best practices and practical case implementations, we offer insights into how aligning these data pillars can enable organizations to build resilient, responsible, and results-oriented AI ecosystems.
Amit Jha (Fri,) studied this question.