The degree to which data is accurate, complete, consistent, and fit for its intended use. High data quality is foundational for trustworthy AI outputs. Poor quality data increases the risk of misrepresentation and hallucination. For more on governance frameworks, see our research on data governance in generative AI.
Data quality directly affects the reliability and trustworthiness of AI system outputs. Organizations with poor data quality face higher risks of AI-generated errors and misinformation.
AI systems depend on high-quality training and retrieval data to produce accurate, reliable outputs. Quality issues in source data propagate to generated content.
Data quality issues in product catalogs can lead to incorrect AI recommendations.