In this episode, Laura Fu interviews Habib Basiri, a leader in AI product management, discussing the critical role of data governance and knowledge graphs in building trustworthy AI systems. They explore how enterprises can evolve their data strategies to enhance AI adoption, the importance of transparency in AI models, and the future of AI with verticalized graphs. Habib emphasizes the need for proactive governance and the integration of data management as a core feature of AI products.

Takeaways

Knowledge graphs play a crucial role in understanding data semantics.

Trust in AI is built through transparency and explainability.

Data governance should be proactive, not reactive.

Companies need to automate governance to avoid bottlenecks.

The maturity of data governance directly impacts AI adoption.

Verticalized graphs will enhance the accuracy of AI models.

Real-time data access is essential for effective AI.

Zero copy data management reduces compliance risks.

Investing in governance platforms is crucial for long-term success.

AI governance is a product feature, not just a compliance requirement.

Keywords

AI, data governance, knowledge graph, trust in AI, enterprise AI, data transparency, AI adoption, verticalized AI, real-time data, AI strategy