Full Ratchet: 161. Why SaaS is not a fit for VC and How AI Compounds Competitive Advantage (Ash Fontana)

Podcast Notes Key Takeaways

• Most VC firms are not “focused funds” – they’re more general (they invest in a wide range of companies across many different fields). This is different from Zetta – they only invest in AI & machine learning companies.
  • Focused funds get a 16% higher multiple on invested capital and a 33% higher ROI compared to generalist funds 
• The 4 Phases of AI:
  • Phase 1 (low risk): AI applied to consumer applications
    • Ex. – Google and Amazon giving recommendations
  • Phase 2 (slightly higher risk): AI applied to enterprise SaaS companies
    • Ex. – CRMs suggesting leads
  • Phase 3 (high financial risk): AI-centric applications that completely replace a workflow
    • Ex. – Using AI tech to estimate damage on a car, computer vision in autonomous cars, etc.
    • We are currently in Phase 3
    • The key metric for phase 3 AI: Is the efficacy better than a human?
  • Phase 4: (very high financial risk): Applications we haven’t considered before
    • Ex. – Using AI to optimize data center use or energy flow across an electricity grid, making medical diagnoses, etc.
  • Note – In many cases, even if an AI tech has better efficacy than it’s human counterpart, it will still incur adoption risk. Many people are not ready to trust AI as a total replacement for human judgment.
• AI itself shouldn’t be feared. However, AI can create monopolistic power held by a few companies– this is something to be concerned about.

Ash Fontana of Zetta Venture Partners joins Nick to discuss Why SaaS is not a fit for VC and How AI Compounds Competitive Advantage. In this episode, we cover:

• Categories of AI that Ash is most interested in
• The difference between real AI and AI-enabled companies
• Why SaaS will cease to be investable by VCs
• The current AI stage of adoption
• How he times the market
• The four phases of AI
• What phase of AI they invest in
• How AI is and will be affected by limited data
• How startups can compete for talent w/ GAFA (Google, Amazon, Facebook, Apple)
• The moats being created by their AI-first portcos
• How they think about metrics and milestones for AI-backed companies
• If AI should be feared
• and finally we wrap up w/ Ash's thoughts on Chris Dixon's position that we will see a movement from centralization back to decentralization in tech-- and the role that AI will play

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