2 The role of data stewardship in AI transformation: Origins, quality, and reliability As organizations adopt AI to assist in business decisions, they must ensure that these systems can provide correct and reliable results. The data grounding AI responses must be available, consistent, and well-documented. Data stewardship supports trustworthy Transparency: Knowing where data AI by implementing governance policies comes from and how it changes helps that track where data comes from, check confirm the accuracy of AI-generated its quality, and ensure its reliability and outputs and ensures regulatory accuracy. These practices build the compliance by providing a clear foundation for AI systems that deliver understanding of the data’s history. dependable insights, enabling informed and confident decision-making. Traceability: Data lineage allows organizations to trace errors or Data lineage: inconsistencies back to their source, Understanding origins and simplifying troubleshooting and changes to information data correction. Impact analysis: Understanding how Data lineage tracks data’s journey through data is used by generative AI tools an organization. It documents the data’s helps assess the potential impact of origins, transformations, and destinations. changes in data sources or processing For AI-powered businesses, understanding methods on output accuracy and data lineage is vital for several reasons: business outcomes. 9