Universities and school systems are rushing to embed AI tools while confronting gaps in the data and governance that underpin them. Reports show vendors and tech giants are rolling chatbots and automated tutors into classrooms, even as faculty and administrators warn the tools can erode instruction if trained on poor or biased data. Education leaders and IT offices are increasingly focused on data quality, metadata standards and access controls after early pilots produced inconsistent results. Experts cited in recent coverage argue institutions must treat data stewardship as a core operational function — not an afterthought — to make AI trustworthy and scalable. "Data governance" here refers to the policies and technical controls that ensure data used by AI is accurate, auditable and compliant with privacy rules. Campuses that move ahead without governance risk low adoption, student harms and compliance headaches; those that invest in cleaning, documenting and auditing datasets stand to realize reliable AI benefits for advising, assessment and administrative automation.