Why augmented intelligence (not automation) will define enterprise AI

About this episode

Vivek Vaidya discusses the importance of augmented intelligence over automation in enterprise AI and the role of data architecture and knowledge graphs in successful implementations.

Most enterprise AI failures aren't model problems—they're data architecture problems. Vivek Vaidya, serial entrepreneur with 25+ years building enterprise software and current CTO/Co-founder of super{set}, explains why vector databases alone can't solve enterprise AI and why knowledge graphs are foundational for production systems. He breaks down the critical difference between augmented intelligence (AI proposes, human approves) versus full automation, details how governance layers must respect existing enterprise data policies, and reveals why non-deterministic LLM outputs create compliance nightmares that kill enterprise adoption. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info .

People in this episode

Host: Tom Chavez

Guest: Vivek Vaidya

Topics covered

• augmented intelligence
• enterprise AI
• data architecture
• knowledge graphs
• governance layers
• compliance

Keywords

• augmented intelligence
• enterprise AI
• data architecture
• knowledge graphs
• compliance
• LLM outputs
• automation

Mentioned in this episode

Organizations: super{set}

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