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AI serves as a technical copilot for diligence
“AI as a technical co-pilot for diligence is actually one of the most interesting use cases for AI as an investor right now. If you come across a really interesting company in a field that you know a little bit about but you're not an expert in, you can get really, really deep within the matter of hours, and then pull in human experts to help you to go the last mile. Whereas five years ago, it would have been this mad scramble, calling people, trying to assemble folks that might have taken days or weeks.”
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Investors use LLMs to challenge internal arguments
“They're using tools like Cloud and Chatch GPT to poke holes in them. What am I missing? Where's my argument weakest? Investors for decades have not had access to the kinds of tools that they need to really operate their businesses in a data-driven way.”
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AI automates complex Excel-based financial modeling workflows
“You can go into Excel, hook it up with Cloud, hook up Cloud with Standard Metrics, and then ask it to do a discounted cash flow. It will just build it for you. It's amazing. People are going to be able to spend more time on what they're truly passionate about.”
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Data centralization powers smarter private market decisions
“When I was at Spark... I started realizing that very few investors in the private markets really had access to great software. It was this cottage industry that had suddenly grown a lot and become very competitive and very global, but software hadn't yet caught up. If people had access to better data, they could make better decisions.”
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AI lowers barriers to understanding academic research
“I think that as a VC, having the ability to tailor the output of a model to meet you where you're at from an understanding perspective is one of the most useful aspects. Opening up a 10, 15 page long academic paper full of citations is extremely intimidating. The AI can remove some of that barrier.”