Trustworthy AI systems begin with trustworthy data operations. Organizations need repeatable acquisition, annotation, validation, governance, and audit practices so every dataset can be understood and improved over time.
This article outlines the core controls teams should establish before scaling AI data programs, including documentation, quality gates, risk review, and continuous feedback loops.