1 Strengthening data governance for AI transformation Every enterprise has policies and processes governing data usage. Data governance frameworks vary in maturity and comprehensiveness, but few have been fully optimized for AI. While many data governance best practices stay the same, such as ensuring data accuracy and consistency, other aspects need updates to maximize AI investments. Let’s look at a few key areas. Data visibility Detailed knowledge of data flow within launch, governance must now extend to managing AI-generated content, AI systems makes it possible to find and mitigate unauthorized or inappropriate ensuring that project-related documents, communications, and insights produced use. This visibility helps support security and compliance, protecting sensitive data by AI are secure. This means implementing safeguards so that only authorized team to maximize AI value. members can access and use AI to analyze or summarize project information. Traditional data governance has focused on knowing where data lives and Additionally, by managing data processing controlling access. However, as AI becomes more integrated into business and storage volumes, organizations can operations, data governance needs to better control the operational costs associated with AI. keep up with evolving security needs. For instance, with a highly sensitive product 5