The Impact of Bad Data on Modern AI Projects (and How to Fix It)

The enterprise AI conversation has been dominated by models. Which LLM should we license? Should we fine-tune or use RAG? What about open-source versus proprietary? These are the wrong questions to start with.

The AI boom is exposing a truth that data teams have known for years: most organizations are building on a foundation of poor-quality data. Decades of neglected data strategy are now coming due. The models are powerful, but they're only as reliable as what they're trained on and what they retrieve.