Why 87% of AI projects fail—and how data quality fixes it

Many AI initiatives fall short — not due to the technology, but the data behind it. Incomplete, inconsistent, and ungoverned data leads to biased outputs, eroded trust, and costly failures, with research showing up to 87% of AI projects never reach production due to poor data foundations.

This eBook examines the link between data quality and AI performance, offering a roadmap for AI-ready data environments. Topics include:

• How AI automates rule generation and issue detection
• The role of knowledge graphs in contextualizing enterprise data quality
• A five-step Data First roadmap for AI readiness

Download the eBook to see how aligning data quality and AI strategy drives scalable outcomes.