A Valutics Signal Brief  Opening Insight   Most leaders agree that “good data matters,” yet AI programs continue to break under the weight of inconsistent, incomplete, or poorly governed data. The misconception is simple: people assume that improving data quality automatically improves AI quality. It doesn’t.  Data quality is not a guarantee of AI performance — but it is the minimum condition for AI systems to behave predictably, safely, and intelligently.  The Leadership C

A Valutics Signal Brief  Opening Insight   Many enterprises are rolling out retrieval-augmented generation as the “responsible” way to use generative AI. The idea is appealing: instead of letting a model improvise, ground it in your own documents. On paper, that sounds like an answer to hallucinations and control risks.  The reality is more complicated. Most RAG initiatives quietly assume that any retrieval is good retrieval. If the content you retrieve is noisy, stale, poo

A Valutics Signal Brief  Opening Insight   Many enterprises speak about “AI decisions” as if they are produced in a separate realm, governed mainly by model choice and MLOps discipline. In reality, every AI decision is a data decision.  If inputs are incomplete, inconsistent, biased, or stale, even the most sophisticated model will simply automate error at scale. For many organizations, the fundamental issue is not a lack of AI sophistication. It is a lack of data trust tha