Uploaded February 2026 | Updated September 2026, 2 weeks ago

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🎙️ Future of Data and AI Podcast: Highlight with Emil Eifrem (Founder & CEO, Neo4j)

Should organizations build one massive enterprise knowledge graph — or start smaller?

In this clip, Emil breaks down how companies actually adopt knowledge graphs in practice, why no two organizations look the same, and what Fortune 100 companies get wrong when they try to model everything upfront.

He explains two real-world adoption patterns — and why starting with a business problem and an AI application (not a data dump) is the key to success.

💡 Key insight: The best knowledge graphs don’t start as enterprise-wide initiatives. They grow incrementally, pulled in by real AI use cases — not pushed by abstract architecture plans.

🎧 Watch the full episode: youtu.be/zB76ZORi1wo

🔗 Explore more about the podcast: datasciencedojo.com/podcast

🔹Perfect for: CIOs, enterprise architects, AI leaders, data platform teams, knowledge graph practitioners, and anyone designing scalable enterprise AI systems.

Walk away with a practical blueprint for building knowledge graphs that deliver real business value — without repeating the mistakes of the past.