F1V survey: How VCs use AI for investing, productivity in 2024

By F1V investment manager Oleh Karizskyi, F1V PR writer Olha Dub

Only 1% of VC firms had internal data-driven initiatives in 2022, but the trend has increased over the last two years. More funds are subscribing to ready-to-use AI platforms, building their own, or at least planning to start adopting AI in the coming months.

To better understand how investors use AI, Flyer One Ventures has surveyed global VC firms of different sizes and geographies in partnership with VC Platform Global Community, Kapor Capital, and Getproven.

Here are some key takeaways from our research.

Most VCs adopt AI to be more productive at work

Almost all respondents say using AI helps them increase operational efficiency.

Roughly half of them use AI for content creation. About a third of VCs are trying to streamline sourcing new startups, thesis development, and market research. One-fifth uses AI for due diligence, portfolio management, and founder outreach.

70% of the respondents are adopting AI in several areas, with about half of them focusing on 4-8 directions listed in the infographic below.

Half use ready-made AI software, other half develop custom tools

Approximately 55% of our respondents report their VC funds use off-the-shelf software, while 45% have custom AI tools (or are currently developing them).

Funds mostly design their own tools for summarizing updates from portfolio companies, sourcing new companies, and conducting market and trend research.

Tools for analyzing financials, predicting startup success, and creating application forms are less popular.

The larger the firm, the more likely it is to develop custom AI tools and the less likely to use off-the-shelf tools. Among firms that don't develop AI tools and only use ready-made software, over half are small funds and only a third are mega-funds*.

Beyond the above-mentioned uses of AI, here are the most interesting examples of AI tools our respondents have developed:

• Tools that help find advisors, customers, talents, and diligence opinions faster.
• Tools that write a 2-line description for every company in a pipeline.
• Tools based on a customized ChatGPT for pitch deck reviews and AI transcriptions.
• Tools that move data from Salesforce, clean up notes, and find data connections.
• Chrome extensions that summarize LinkedIn profiles and articles.
• Chatbots for navigation within a knowledge base and interview analysis.
• Personal platform assistants that help investors stay on track with everything from sourcing to founder relations.
• Assistants that review pitch decks based on an investment thesis and generate an initial analysis of each new startup in the pipeline. This analysis is then automatically added to a new investment memo and linked to the Affinity CRM.
• Tools that visualize quantitative and qualitative data about the portfolio's performance and highlight trends.
• Tools that create reminders for teams, such as when to update cap tables.
• Tools that link various SaaS tools to help avoid duplicating data.

About 1/3 of VCs have in-house team or contractors for building AI tools

Among firms that develop their own AI tools, nearly half have at least one in-house employee dedicated to this task (usually combining it with other work).

About half of large funds and mega-funds employ an in-house tech team or collaborate with an agency or contractor, while medium and small firms do so at least twice as rarely*.

Most VC firms have no AI strategy

Although most funds don't currently have a comprehensive AI strategy, almost all respondents said their firms are already using AI in their work or are taking the first steps in that direction.

Two-thirds of mega-funds and one-third of large funds have an AI strategy; among medium and small firms, only 15% do so, too*. Most firms of any size that have a defined strategy develop custom AI tools.

Nearly half of VCs admit AI streamlines their work

Approximately one-third of the respondents had to learn new skills to work with AI tools, while about 10% saw some of their tasks replaced by AI.

They believe these tools make their work more efficient and help automate routine tasks, and nobody expressed concern about AI taking their job in the future.

Almost half of VCs say they haven’t allocated any budget for AI initiatives in 2024

About 40% of funds, regardless of size, say they have allocated up to $10k for AI activities in 2024.

Most small and medium-sized firms report allocating up to $10k, while large firms and mega-funds typically allocate $50-100k; or even more*.

2/3 of respondents plan to adopt new AI tools over next 12 months

In the coming months, many VC firms plan to adopt new AI tools for streamlining both inbound and outbound deal flow. These tasks include sourcing and evaluating new startups — including assessing their compliance with the VC firm's thesis — market research and due diligence, investment memo creation and founder outreach.

To optimize interactions with portfolio, many firms plan to integrate AI tools for summarizing investor updates and monitoring portfolio companies’ performance.

Some funds will work on increasing internal productivity. For instance, a few consider establishing AI knowledge management systems like Danswer, which finds and analyzes any data inside a company. Others want to use tools that find and analyze documents.

A few firms also want to use AI more frequently for content creation and marketing. Part of the funds will focus on enhancing their existing custom tools and connecting them, while others will test multiple ready-made tools inside their teams.

Although over one-third of VC firms still don’t have specific plans for adopting AI, most say they are currently discussing opportunities and their needs, and conducting research.

AI tech stack mapping

These seven external AI tools are currently the most popular among VC firms, making up about 70% of all mentioned off-the-shelf tools: ChatGPT, Perplexity, Affinity, Claude, Microsoft Copilot, Fireflies, and Notion AI.

Respondents of this survey

We got answers from 108 platform managers, investors, and executives of various levels.

About two-thirds of them represent U.S. funds (70), the rest represent European (20), Canadian (4), Brazilian (3), Israeli (2), Australian (2), and other funds (7).

How big are these firms?

• Nearly half of them are small-sized, having up to $250M AUM (45 funds).
• Medium firms with AUM of $250M to $1B represent one-fifth of the group (25 funds).
• Large funds with AUM of $1B to $5B represent one-third of the group (30 funds).
• Less than 10% are mega-funds with AUM over $5B, they’re from the U.S. and Canada (8 funds).

*Small funds have < $250M AUM; medium funds have $250M – 1B AUM; large funds have $1B – 5B AUM; mega-funds have > $5B AUM.

Subscribe to our LinkedIn newsletter to get one useful article every week via email and on LinkedIn. We promise each story to be insightful and take less than 5 minutes to read.

More posts like this: