TDWI Snapshot | The State of Data Quality: New Demands in the Age of AI
March 30, 2026
Data quality is already critical to analytics, but generative AI and agentic AI introduce more complexity and new challenges.
AI systems introduce new points where quality must be assessed, including the quality of input data (including unstructured data), the model itself, and the outputs it produces. Additionally, problems such as hallucinations, bias, or inconsistent reasoning can arise even when input data is strong.
In a recent TDWI webinar, Fern Halper, Ph.D., VP of research at TDWI, spoke with Millie Beetham, VP of GTM at ZoomInfo, about the current state of data quality and what changes with AI. The conversation underscored some critical insights around traceability and metadata as essential standards for managing AI-driven data, the importance of data quality metrics for AI, and the shifting definition of “good enough” data quality.
Download this snapshot report to learn more about research findings and insights raised during this discussion!