EPISODE · Apr 13, 2026 · 31 MIN
Why augmented intelligence (not automation) will define enterprise AI
from The {Closed} Session
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.
What this episode covers
Dissect why enterprise AI fails at the system layer, not the model with super{set}'s Vivek Vaidya.
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Why augmented intelligence (not automation) will define enterprise AI
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