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Rahul Agarwal
Founder | Agentic AI... • 5h
AI projects don’t fail on models. They fail on messy, unmanaged data behind the scenes. Data governance rarely gets attention when it works, but takes all blame later. And most teams only realize its importance after something critical breaks. Here’s what experienced teams learn the hard way: Strong governance stays quiet Broken governance gets loud Flawless data is a myth, and chasing perfection will slow everything down. Define what’s usable Then move forward Leadership supports the idea, but hesitates when budgets and tradeoffs appear. Tie it to impact Or it won’t last Most people hear “governance” and think friction, not speed or outcomes. Show the value Not the rules Ownership gets blurry fast when everyone wants insights without responsibility. Make it visible Reward accountability Tools don’t fix this problem, because most failures come from habits and workflows. Focus on behavior Before platforms This isn’t a one-time effort, it’s something that needs to live inside daily work. Build it into routines Not side projects If your data foundation is weak, AI will only scale the problems faster.
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