In many respects, this lack of trust is understandable. Data issues can cause AI to produce false or biased results, potentially creating regulatory risks and reputational damage. Problems don’t just stem from data quality either: a lack of insight into freshness, fitness for purpose, explainability and lineage can also have serious repercussions for the business. Lineage goes hand‑in‑hand with data quality because it provides the transparency needed to assess and maintain quality. Without understanding the full journey of the data — where it originated, how it was transformed, you need visibility into the full life cycle from source to decision.