TigerEye and Data Management — Why AI Needs Progress Over Perfection

Marc Benioff said the quiet part out loud during Salesforce's earnings call:

“Those that want to deploy artificial intelligence agents that draw on extensive data will need to clean up their data first.”

Sure, clean data helps. But most teams aren’t starting from perfect, and that’s the real problem.

The truth is, AI tools need to work with the data you already have, good, bad and everything in between.

At TigerEye, we don’t ask GTM teams to stop what they’re doing and clean up everything. We show them what’s working, what’s not, and how to move forward anyway.

Because visibility isn’t just about hygiene. It’s about speed, alignment, and knowing where to act.

Perfect data is a goal. Progress is what actually drives results.

As Ron Miller wrote in his FastForward newsletter, “Those organizations dealing with legacy data problems need to think more deeply about, and put more resources into getting their data in order.”