VCs love to bang on about how AI is disrupting every industry in the biggest technology revolution since the internet. But the VC industry itself is also feeling the winds of change — and AI could have a huge impact on how investors do their jobs in the future, or if they have jobs.
“I think that you are going to see AI-first or AI-only funds,” says Akshat Goenka, partner at London-based early-stage firm Moonfire.
There are already plenty of “data-driven” VCs, like Moonfire, but the recent boom in AI agents — apps using large language models (LLMs) to automate tricky tasks without a human involved — could more dramatically change the industry.
Some investors, like Goenka, say it’s not impossible to imagine a future where an entire deal — from sourcing to decision-making to even the founder accepting the offer — is fully automated.
“There’s at least one completely autonomous fund with zero human partners” — No Cap, which bills itself as the “world’s first AI angel investor” — says Daniel Dippold, who runs the German accelerator and YC challenger EWOR. “We’re seeing a wave of solo GPs using AI as a force multiplier.”
The future: Democratised dealflow and fully-automated decision making
“If you think about the core competencies [of VC] being access, judgment, networks, etc., I think AI has a pretty clear-cut way of reshaping some of those,” Goenka says. “I think dealflow will get democratised. As more and more sourcing tools are widely accessible, the traditional advantage that some firms have of deep networks or local proximity goes away a little bit.”
Five-year-old Moonfire is a firm without those historic advantages. Instead, it has more than twice as many engineers (five) as it does partners (two) on staff. VCs already use digital scrapers to process and collect thousands of data points from blog or social media posts, product launches, GitHub activity, media coverage and pitch decks — and now, with machine learning, they can parse that data to “correlate patterns and identify potential companies that are exciting,” says Goenka.
“All the data parts — the pattern matching, the benchmarks of the metrics — will be more and more [automated],” thinks Jonathan Userovici, Paris-based general partner at VC firm Headline.
Headline has already built proprietary, in-house tools both to source and diligence startups, with a team of 20 engineers working away on algorithms and AI. “We have probably thousands and thousands and thousands of sources of data points now,” says Userovici.
EWOR is already using AI agents to query its database to “find the perfect connections in our network — essentially creating a talent-matching engine that operates at a scale no human could,” says Dippold.
It’s also using AI to analyse applications for its accelerator, and Dippold believes AI might even surpass humans when it comes to pattern-matching for founder potential: “When this happens, capital will become even more commoditised than it already is.”
AI-only funds?
One other big change: funds that are fully run by AI — something that’s already starting to happen, as Dippold points out.
We’ll eventually see “autonomous investment entities”, says Dippold — but “how quickly and whether they’ll outperform human-led funds” remains to be seen.
Most VCs remain sceptical about the entirely human-free investment model. According to the 2025 Data-Driven VC report, 94% of respondents believe the augmented human-in-the-loop model will dominate VC moving forward, up from 75% in 2024; only 5% believe the quant model (with no humans involved) will take the lead. (Both years’ surveys had over 130 respondents.)
But even a heavily AI-augmented future will have a notable impact on the industry. Many VCs think teams will be leaner moving forward, with fewer opportunities for human analysts and associates.
Over a third (38%) of respondents to the Data-Driven VC report think investment teams will become smaller as a result of AI.
How can VCs stay competitive?
If everyone is using the same AI tools to see every deal or automate the dealmaking process in the future, what sets them apart?
The interpersonal and emotional skills that it takes to actually win deals, VCs say. They believe the rapport, connections and relationships with founders isn’t something AI can replicate.
“AI will commoditise certain aspects of venture capital, but that only increases the value of what can’t be automated: deep operational expertise and a community of true outliers building together,” Dippold argues.
Fully embracing AI, on the other hand, may be a differentiator itself: “I don’t think everyone is capable of adopting AI as robustly as others,” argues Goenka. “If you have a VC firm which has a very specific way of working over a long period of time — because VC, by definition, is so top-down, partner-down, partner-led — it’s hard to suddenly, retrospectively change and alter how you do things,” Goenka says.
Of course, they’re biased, but Userovici and Goenka believe the funds that will have an edge are the ones that have proprietary models or internal tech, unique training data or hyper-personalised agents.
Ultimately, Goenka believes whatever VCs do with AI will come down to how founders respond, and if they care. If they react very negatively or positively to certain aspects of the experience, that might change things.
“What founders want, and where the best founders lean towards, should dictate to a certain degree the strategy of a VC firm.”
Read the orginal article: https://sifted.eu/articles/ai-impact-vc-investing/
