Post by GenAI Works

AI on bad data is worse than no AI. Everyone wants to be AI-first in 2026. Boards love the phrase. It sounds sexy on paper. Truth is, most "AI transformations" are data cleanups wearing a costume. Because AI amplifies whatever you feed it. Feed it chaos → automated chaos. Feed it clean, owned, governed data → compounding advantage. Over 80% of AI projects fail (RAND). Missing or unusable data sits near the top of the causes. So here's what "clean" actually means. 5 checks before any model touches your data: - One named owner per critical dataset. A person, not a committee. - One source of truth per metric. If revenue lives in 3 dashboards, you have 0. - Decide how old data can be before it's a liability. Write it down. - Every number can answer "where did you come from?" And a shortcut: don't clean all 500 tables. Start with the 5 that feed money decisions. Data-first looks slower in Q1. By Q4 it's the only bridge still standing. Do you agree?