As every CIO knows, AI success hinges on rock-solid data practices. But as CEOs and boards have emphasized digital transformations in recent years, funding for data management transformation efforts has been piecemeal at best. Now, with AI atop the CEO agenda, many CIOs find themselves in a bind, having to also overhaul data operations and address years, or decades, of accumulated data debt. If your enterprise has data debt, AI will expose it. In fact, data debt can lead to devastating failure rates with AI projects. For technology leaders, there’s no time like the present to pay down this debt with a comprehensive remediation strategy. Data debt can arise for a variety of reasons, including old and outdated data management practices, shortcuts and compromises in infrastructure to meet near-term goals, poorly documented data sources, and inefficient data storage practices.

Full report : With data quality and governance key to AI success, IT leaders — and their CEOs — can no longer overlook data debt. Experts offer tips for remediation.