Why the Best AI Investors Don't Invest Alone: how collaboration sharpens judgment and diversifies early-stage AI portfolios
About this session
Early-stage AI is hard to judge and hard to diversify alone. Research on business angel returns points to a sweet spot of 20 to 25 startups, yet few investors can source, screen and support that many companies on their own. This talk shows how collaboration helps on both fronts. We look at six business questions that matter more than technical depth when assessing AI startups, and how investors with different backgrounds test each one from a different angle. We walk through a real group decision process, from pitch to vote to investment, and zoom in on one portfolio company to show what that judgment looks like in practice. We also stay honest about what collaboration does not change: risk, illiquidity and the need to accept group decisions. You leave with a practical checklist and one question about your own blind spots.
Speaker
Key takeaways
- Why 20 to 25 startups is the research-backed sweet spot for early-stage portfolios, and why it is hard to reach alone.
- Six business questions for judging an AI startup, and how different investor backgrounds sharpen each answer.
- How a structured group process (pitch, vote, due diligence, invest) works, and what it does not remove: risk and illiquidity.