Why AI Projects Fail: An Oracle Strategist on Data, Guardrails & the 70% Problem | Diganta "Digs" Sen Gupta
Pivoting to Technology Adoption
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Show Notes
Why do 70% of AI projects fail? In this milestone Episode 100, Donna P. Mitchell sits down with Diganta "Digs" Sen Gupta — Forbes Technology Council member, IEEE AI Governance Committee member, and Oracle enterprise architect with 25+ years of experience — to break down what executives must understand about data readiness before any AI initiative.
WHAT'S COVERED:
- Why "everyone from bedrooms to boardrooms" talks AI but most projects fail
- The data silo problem destroying enterprise AI initiatives
- How Oracle went from database company to multi-cloud AI partner
- RAG, vectorization, and semantic search explained simply
- The guardrails executives must put in place before any AI project
- How blockchain creates "trusted data" for AI applications
- AI's future in healthcare: diagnostics, patient records, and beyond
(00:00) Welcome and Introduction
(01:01) Digs' Journey With Oracle — 2007 to Present
(02:49) Oracle's Transformation: Database to Cloud
(10:28) Why AI Projects Fail: The Data Problem
(16:11) RAG and Vectorization Explained
(21:34) The Three Mistakes Executives Make With AI
(37:04) AI in Healthcare: The Future
ABOUT THE GUEST: Diganta "Digs" Sen Gupta is a Forbes Technology Council member, IEEE AI Governance Committee member, and Oracle enterprise architect with more than 25 years of experience in enterprise technology transformation. He specializes in AI governance, data strategy, and multi-cloud architecture across healthcare, financial services, and public sector.
ABOUT DONNA P. MITCHELL: Founder of The Transformation Authority™ and CEO of Mitchell Universal Network LLC. Official Member of Forbes Business Council. 48 years of Fortune 500 experience across 5 industries, enabling 150,000+ professionals.
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