Documented data lineage (option B) is a cornerstone of mature data governance. The ISACA AAIA™ Study Guide highlights that "effective data governance for AI is characterized by the organization's ability to trace and document the origin, transformation, and use of data throughout its lifecycle and within AI models." This documentation provides transparency, supports accountability, and enables effective risk management.
While regular data quality audits (option C) are important, they do not, by themselves, ensure transparency or traceability. The number of projects (option A) and budget allocation (option D) are not directly indicative of governance maturity.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: " Data Governance in AI: Data Lineage and Traceability "