Bad data is expensive for AI and for the business. Gartner estimates poor data quality costs organizations an average of $12.9 million per year. This guide explains where those losses come from and the practical steps leaders can take to strengthen data quality in AI.

Process debt builds as teams grow faster than workflows, documentation, and handoffs are updated. The result is friction, slower delivery, and higher risk. This post explains how process debt shows up and practical steps to reduce it.