Data Before AI: Building the Right Foundation for AI Readiness

About the Session

AI is a top priority for businesses, but without a strong data foundation, AI efforts fail. This session highlights why data maturity must come before AI adoption, ensuring organizations don’t waste time and money on unreliable models. Many organizations rush into AI without properly managing their data. Poor data quality, inconsistent governance, and siloed information lead to flawed AI outputs, legal risks, and lost trust. This talk provides a structured approach to AI readiness, covering: - Data governance, quality, and accessibility as prerequisites for AI success - How to assess AI readiness based on data maturity - Real-world case studies of AI failures caused by poor data management - Why AI adoption fails without a solid data foundation - A step-by-step guide to building AI-ready data ecosystems - Actionable strategies to fix data quality and governance issues before investing in AI

Speaker

Ayoade Adegbite

Specialized Data Analytics Mentor at CareerFoundry, Analytics Engineer.