Why 95% of AI Projects Fail, Anthropic still at $2T?, and Why AI Is Still in the First Inning
Studio VC Co-Founder and Managing Partner Joseph Coyne sits down with host David Weisburd to explore why enterprise AI remains in its earliest innings. They examine why 95% of enterprise AI pilots fail, how proprietary data behind corporate firewalls creates enduring moats, and how physical AI applications in healthcare and motion capture are paving the way for next-generation robotics. Coyne and Weisburd also analyze venture valuations, business model transitions from SaaS to usage-based pricing, and how to underwrite foundation models like Anthropic and OpenAI.
- More than 80% of the world's data remains locked behind corporate firewalls, out of reach for public foundation models such as Anthropic and OpenAI. Read →
- Roughly 95% of enterprise AI pilots fail because corporate buyers deploy generic foundation models against standard workflows without proprietary data behind the firewall. Read →
- Late-stage foundation model rounds require massive market capture assumptions that clash with near-zero switching costs across major LLMs. Read →
- Ninety-five percent of enterprise AI pilots fail to reach production because pure technical tools fail to address legacy workflows and regulatory constraints. Read →