Most AI projects fail because the data isn’t ready

What’s happening: Companies jump into chatbots or automation before fixing data access, permissions, and quality. AI then gives inconsistent answers, or it can’t find the right information.

FYNGA take: Start with a “Data Readiness Sprint”:

  • Identify where your knowledge lives (SharePoint, Google Drive, emails, CRM, ERP)
  • Clean + tag the most-used documents
  • Set role-based access rules
  • Build a small AI pilot that answers only from verified sources

Why it matters: When the data foundation is right, AI becomes reliable—and adoption increases fast.