Should AI Touch All Your Data? | Deep Geeks ep06

Can AI be your data QA? A look at how retailers use AI to surface data quality issues before they reach decisions. https://www.weka.io/podcast/one-size-fits-none-what-retail-reveals-about-ai?utm_source=youtube&utm_medium=social Most teams are not ready to point AI at every system they own and let it start making calls. But there is a narrower job AI is very good at right now: acting as a QA and QC assistant across messy enterprise data. In this clip from the WEKA podcast, the conversation turns to what retailers can do today that was out of reach five or ten years ago, and why reconciliation is the obvious starting point. The framing is simple. Instead of unleashing AI on all your data to ask open questions, you give it a bounded task: reconcile these two sources, flag the naming inconsistencies, tell me what does not make sense, explain what this field actually contains. AI brings the problems to light. People still decide what is worth fixing, what can be fixed, and what never makes it above the line, because every business has a finite list of priorities and not every data quality issue earns a spot on it. It is also work humans find tedious and boring, which is exactly the profile of a good AI use case. Listen to the full episode: One Size Fits None: What Retail Reveals About AI: https://www.weka.io/podcast/one-size-fits-none-what-retail-reveals-about-ai?utm_source=youtube&utm_medium=social&utm_content=podcast-episode More from WEKA: https://www.weka.io/?utm_source=youtube&utm_medium=social&utm_content=homepage Subscribe for more AI infrastructure content: https://www.youtube.com/@WekaIO?sub_confirmation=1 About WEKA: WEKA NeuralMesh™ is the data platform built for AI, delivering the performance and efficiency needed to run agentic and LLM workloads at production scale. #DataQuality #WEKA #EnterpriseAI #RetailAI