Many organizations are eager to harness AI but face setbacks when their data is incomplete, inconsistent or poorly governed. These gaps lead to biased, untrustworthy outputs that limit adoption and slow innovation. This resource explores how data integrity, through quality, integration and governance, provides the foundation for trusted, AI-ready data.