AI promises major gains in innovation, efficiency, and competitive advantage. But to achieve that, organizations need more than tools—they need accurate, reliable and accessible data. Right now, many are held back by siloed systems, legacy infrastructure, and outdated data practices. “AI really isn’t experimental anymore,” says Stephen Catanzano, Senior Analyst at the Enterprise Strategy Group (part of TechTarget). “Everyone is on a journey towards reaping the benefits of what AI can deliver—competitive advantage, innovation, cost savings, and more.

Yet most organizations still struggle with fragmented data, inconsistent definitions, and governance gaps. Without a strong foundation, AI can’t deliver the results leaders expect. This paper explores how a mature data fabric, supported by a strong metadata strategy, helps overcome these challenges and how unified data access, semantic consistency, and real-time governance pave the way for scalable, trustworthy AI.