AAISM Domain 1 AI Governance, Program Management Practice Test

Data stewards/owners are accountable for data governance and data quality across the organization. They define and enforce the standards that data must meet—such as accuracy, completeness, consistency, timeliness, and proper metadata—ensuring the data used by AI is reliable and well-managed. This role also covers data definitions, lineage, cataloging, access policies, and ongoing quality monitoring, which together establish trust in AI outputs. Data engineers, while they build and maintain the data pipelines that supply data, typically execute and operationalize those standards rather than own them. AI ethicists focus on ethical considerations in AI applications, such as fairness and transparency, not the formal governance of data quality. Privacy experts concentrate on protecting personal data and compliance with privacy laws, which is essential but addresses a specific aspect of governance rather than the overall data quality governance for AI.