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Original article date: Sep 08, 2026

The Hidden Reason Your AI Implementation Is Underperforming: Dirty Data

September 8, 2026
•
5 min read

The Hidden Reason Your AI Implementation Is Underperforming: Dirty Data

Most AI implementations aren't failing because of the AI -- they're failing because the data underneath it is a mess. Zac Choi, founder of Big Context & Company, has spent two decades watching this problem develop.

Key Takeaways

  • LLMs are probabilistic tools, but enterprise data work is deterministic -- structurally incompatible without a clean data estate.
  • AI agents can't make reasonable guesses about messy data the way humans can -- and get it wrong at scale.
  • Choi's previous startup, String AI, was built and sold to a telco; Big Context & Company targets the same root problem.

The primary users of enterprise data are increasingly going to be AI agents, not humans. The infrastructure most companies built was designed for humans asking predictable questions. Cleaning it up is the first step to making any AI implementation reliable.

Read the full article on Entrepreneur.

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