Discover more from Data-driven VC
Insights From the Data: 10 Charts About the State of AI
DDVC #42: Where venture capital and data intersect. Every week.
👋 Hi, I’m Andre and welcome to my weekly newsletter, Data-driven VC. Every Thursday I cover hands-on insights into data-driven innovation in venture capital and connect the dots between the latest research, reviews of novel tools and datasets, deep dives into various VC tech stacks, interviews with experts, and the implications for all stakeholders. Follow along to understand how data-driven approaches change the game, why it matters, and what it means for you.
Current subscribers: 10,952, +301 since last week
Brought to you by Affinity - Insights you need to find, manage, and close more deals
Get all of the data and insights you need to benchmark your firm’s performance against Europe’s investment leaders. Plus, take a deep dive with us to answer the question: Where did all the unicorns go?
Today is a special episode as I combine my occasional “Insights from the data” series with my deep passion for AI (check out my latest “AI Cheat Sheet” in case you missed it) and share the results of an analysis that I recently conducted with my team at Earlybird.
Extracts of our research got exclusively covered by leading German business newspaper Handelsblatt earlier this week and I’m happy to share the most important takeaways (including some nice graphics prepared by Handelsblatt - thank you!) here with you.
1. Silicon Valley is the epicenter of AI innovation
2. North America is home to by far the most AI startups
3. Estonia produces most AI startups per capita
Join 10,900+ thought leaders from VCs like a16z, Accel, Index, Sequoia, and more.
4. US-based AI startups received largest funding rounds
5. The AI funding boom began in late 2021 in North America
6. North America hosts by far the most AI investors
7. Multiple AI hubs evolve across Europe
8. AI hubs evolve around leading universities in Europe
9. Few leading universities produce AI founders at scale
10. The number of AI startups increases gradually from the infrastructure up to the application layer
Methodology: Thanks to Earlybird’s EagleEye, we’re able to track 3+ million companies on an extremely granular level of detail over time. Moreover, our semantic algorithms allow us to automatically classify companies based on different sources (such as the content of their website or their official company descriptions in the public registers) into our internal sector and technology clusters. Hereof, we can comprehensively identify all AI companies (and the respective investors) without the company explicitly stating terms like “AI”, “ML”, or “Deep Learning”. Clusters evolve on the meaning of a company value proposition, not some deterministic words.
For the sake of this analysis, we removed the noise and only included private companies that received more than 500k US$ in funding within the last 5 years. Subsequently, we analyzed the resulting sample across dimensions such as location of the headquarter, their investors, educational backgrounds of the founders, and a lot more. Hope you find some value in it.
Thank you for reading. If you liked it, share it with your friends, colleagues, and everyone interested in data-driven innovation. Subscribe below and follow me on LinkedIn or Twitter to never miss data-driven VC updates again.
If you have any suggestions, want me to feature an article, research, your tech stack or list a job, hit me up! I would love to include it in my next edition😎