10 Mistakes to Avoid on Your AI in VC Journey
Learnings From Digitizing a 27 Year Old Investment Firm
👋 Hi, I’m Andre and welcome to my weekly newsletter, Data-driven VC. Every Tuesday, I publish “Insights” to digest the most relevant startup research & reports, and every Thursday, I publish “Essays” that cover hands-on insights about data-driven innovation & AI in VC. Follow along to understand how startup investing becomes more data-driven, why it matters, and what it means for you.
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I just got back from the “GenAI Wednesday” event in Munich where I gave a talk about “Data-driven innovation & AI in VC”. One of the most frequent questions - not only at the event but also more generally - was where to start your data-driven journey.
As I’m writing this article here burning the midnight oil, I decided to dedicate today’s episode to some lessons learned and 10 mistakes to avoid on your AI in VC journey.
1. Join a community of like-minded peers. You’re not alone.
When I embarked on the journey of making venture capital more data-driven in 2017, I felt lonely. Everyone told me “it’s not possible” and “others have tried” but nobody - except my partners - encouraged me to push for change. The industry was just not ready.
Fortunately, I trusted my instincts, similar to a few other lonely soles I met during my PhD and first years as an investor. We began connecting, exchanging our struggles, brainstorming, and contemplating the future of venture capital through one-on-one discussions. Gradually, these conversations evolved into small WhatsApp and Slack groups, which have been expanding steadily over time.
With ChatGPT and mass awareness for AI adoption, things started to accelerate end of 2022. Suddenly everyone and his dog was looking to become more data-driven and leverage AI. I started receiving numerous questions from other VCs and got invited to many more “AI in VC”, “Data in VC”, “Datahunt”, “VC <> Data”, and similar groups - majority of which became ghost towns quickly as most people wanted to take but few wanted to give. Zooming out, these groups are just too fragmented and not actively managed.
Counting the members across all groups I’m in, I get to around 300. This is in contrast to 20.6k subscribers of Data-driven VC. What about the other 20.3k? Right, you feel left alone with your legacy tool stack and pressure to become more efficient. But you are not. You are part of the big majority that feels lost in the noise. I can see it in the tens and hundreds of DMs I receive every week.
Unfortunately, I cannot answer all messages but I decided to build something more scalable, something better than the fragmented ghost towns: A community platform for everyone seriously interested in data-driven innovation and AI in venture capital. For those who are willing to give and share, and not just take and hide. Those who want to become stronger together, while at the same time keeping your secret sauce and winning an edge.
This is what a community is all about and I will make sure you’ll find everything to run a modern VC firm in one place: Highly actionable content, playbooks and best practices, podcasts and video recordings, tech stacks of similar firms, tool reviews and discounts, database benchmarkings, and most importantly, moderated community channels.
Sign up below to join the waitlist for our Data-driven VC community. There is no reason to be alone.
2. Get top-down support from your GPs.
Once you surround yourself with like-minded peers, you will quickly understand where the industry is heading and what you can do to catch up. Thereafter, you need buy-in from your GPs as any investment in tools and engineering HR will cut from their profits.
So better have a convincing story as the lack of top-down buy-in makes it a no-starter. Make sure you’re all on the same page. How much are you willing to spend? What are the expectations?
3. Laser focus: Define what you actually want.
Many start buying datasets and comparing CRMs without actually knowing what they want. Don’t be one of them. Take a step back and define your firm’s strengths and weaknesses. What works well and what can be improved?
While for some it’s increased deal flow and coverage, it’s better prioritization and access for others. Define your goals and be critical about which initiatives contribute to your North Star. Don’t get lost in the noise and just try to copy what others have done. Even worse, don’t be reactive to the masses of tool providers reaching out. Be proactive, do your home work, know what you want.