When longtime investor Matt Karna started Two Meter Capital this year, he hired just a skeleton team to manage a vast portfolio of more than 190 companies. The firm uses generative AI to do much of the day-to-day portfolio management, tracking how companies are performing and when they might raise another round. Without AI, Krna estimates it would need to hire half a dozen analysts.
“In terms of staffing capacity, if you were taking an analyst class of six, now it's three,” Karna said. “I think a lot of venture funds will start using AI as a tool.”
Silicon Valley has been mesmerized by AI for the past couple of years, with VCs racing to fund all sorts of AI startups. Now, AI is changing VC itself, making an already difficult field for young peers even more difficult and influencing how early-stage startups are funded. go
Firms like Correlation Ventures, 645 Ventures, and Fly Ventures have long used data and AI to help guide investment decisions. Signalfire, a San Francisco firm that has been a leader in harnessing data, developed an expensive platform years ago that tracks more than 10 million data sources. But rapid developments this year are making the use of AI more widespread, several VCs told BI.
Earlier this year, Srichandra Shekhar, a partner at Point72 Ventures, noticed that a startup in his portfolio was having a breakout week.
“Because we're insiders, we saw, 'Wow, the company is doing really well,'” he recalls.
He figured he'd have the data, given Point 72 had access to the company's weekly internal metrics. But he was surprised to discover a wave of interest from other firms that he thought could only be explained by competitors using AI models to comb through publicly available data from thousands of companies. are
“It's not an accident,” Chandrasekhar said. “There are indicators that, if you know how to dig for them on the Internet, will indicate whether a company had a particularly good week, and miraculously seven funds got to them this week. “
Chandrasekhar declined to name the startup or the exact metrics that were so favorable, but says they could include things like product adoption or aggressive recruiting on the sales team. Chandrasekhar predicts that firms that don't use AI will miss out on deals. It will be up to the general partners whether they want to use the technology to eliminate or enhance the role of the junior investment.
“Some of them want better coverage with the same number of people and some will just need fewer people,” Chandrasekhar said. “I want to get better coverage so I can see more great deals.”
Bain Capital Ventures, the venture division of Bain Capital with $160 billion under management, recently built a machine learning model that helps identify impactful companies that the firm's partners can more closely evaluate. Should be taken.
Cristina Milas Cariazzi, a partner at BCV that focuses on fintech and application software, says the model helped her identify a hot startup that wasn't on her radar because it wasn't located in a tech hub. was
“We've seen tremendous growth in this company, and not only that, but also tremendous engagement from their customers,” Melas-Ceriazzi said. “We immediately went out to meet the founder and ended up investing. We wouldn't have known about this company otherwise if it wasn't for this model.”
Back offices can be reduced by up to 50%
Whatever happens to the investment teams, Chandrasekhar expects the size of back offices – handling functions like human resources, administration and financial reporting – to shrink by more than 50%.
“If you go to any venture firm's website, you'll find that half the names aren't doing anything with investments,” Chandrasekhar said. “I think every company's back office is going to be significantly impacted by AI.”
Andreessen Horowitz now employs over 500 people with an investment team growing by 170% over 2017-2021. According to LinkedIn data, General Catalyst employs 259 people while Lightspeed has 300.
“If you look at the big firms, they've gotten bigger in the last few years,” said Andy McLoughlin, managing partner at Encore Capital.
NFX General Partner James Currier wrote a much-discussed column last year explaining why he thinks the use of AI will level the playing field for venture capitalists over the next decade, as That's what software did for stocks and bonds over the past 40 years. .
“Let's be honest: What a typical venture capitalist does — reading, summarizing, and categorizing — is what the big language models already do very well,” Carrier wrote. “We are in the last 10 years of venture capital as we know it. AI is going to remake the startup industrial complex at its core. Venture firms will have to reinvent themselves as a combination of people and AI. “
It is still a human to human business.
Overall, it's not like most VC firms are overstaffed. According to Deloitte, the average firm employs just 14 people.
“They're already too small,” said a partner at a major firm who asked not to be identified, speaking in a spacious conference room in his sleek and mostly empty San Francisco office. “Could you have less people? For what purpose? You're making as much money as it is.”
And the core of making that money depends on charging a hefty management fee for the mystery of venture capital, which most VCs insist is mostly about the gut feeling, intuition, and personal connections that AI can make. Can never change.
“It's still very much a human business,” McLoughlin said. “People want to work with people.”
Uncork only employs one partner and McLoughlin says they won't be replacing him with AI anytime soon.
“I'm sure there's a bunch of AI tools she's using, but the key is being very, very smart and very well trained.”
Converting humans is especially difficult in the early stages, where it's often more about the kernel of an idea with little data for AI to harvest.
“I don't think AI is very good at analyzing things we haven't seen before, and the best venture results often break the pattern,” Mellas-Cariazzi said.
At its heart, venture is not about finding the best deals but about winning them. According to Chandrasekhar, it comes down to the personal relationship between the founder and the investor.
“One of the reasons a founder chooses you is because they specifically want to work with you,” he said. “You spend time building relationships with them, you have dinner with them, you meet their family – whatever you need to do to make them feel like they're really you. Want to work with what you hope is a ten-year marriage.”
Machines are far from it.