With ChatGPT monthly visits at 4.67 billion (up from 1.8 billion in March 2024), it’s clear that the world continues to embrace AI. And the venture capital industry is no exception. As AI evolves, VCs continue to find new ways to incorporate AI-powered solutions to improve efficiency and effectiveness. Ninety-two percent of VCs are using AI in their firms to optimize due diligence, manage relationships, and discover new investment opportunities.
AI is changing how venture capitalists do business in new and novel ways, helping firms tap into new levels of insight and operational efficiency while still prioritizing the relationships that drive successful investments.
Key takeaways
- AI is improving VC productivity by automating research, daily tasks, and identifying high-potential opportunities.
- The overwhelming volume of data in VC can make it difficult to extract actionable insights without the right tools and a thorough understanding of the data.
- Relationship data can be as valuable as financial data in identifying high-potential opportunities.
- Platforms like Affinity with specialized AI capabilities streamline operations, helping VCs make smarter investment decisions and close deals faster.
AI’s role in venture capital
Data is a central part of the venture capital ecosystem. Year-over-year, 49% of investors continue to use four to six data sources when evaluating most deals. Capturing, sorting, and analyzing data at this scale can be challenging and time consuming, so more investors are turning to AI to assist with productivity-related tasks.
In 2025, 64% of VC investors report using AI to accelerate researching companies, up from 55% in 2024. And 76% report using AI to help automate daily tasks, up from 62%.
Notably, there's one thing investors are using AI for less—decision making purposes. While impressive for things like automating data entry and speeding up research, AI is best used as a supplemental tool to support data collection and analysis to give investors the information they need to make better deal decisions.
AI is being used by VCs as a tool to improve key tasks like due diligence and company discovery while increasing efficiency across workflows. While the final decision on whether to invest in a company may not be made by an AI program, it is increasingly informed by the information gathered and analyzed using AI.
The challenges of a data and relationship-driven industry
Along with data, venture capital funds rely heavily on their networks and relationships to find and close high-value deals. And while data and relationships might seem like two distinct entities, in VC they’re deeply interconnected.
Every relationship, every contact is a source of valuable data that should be tracked. Whether it’s file exchanges, emails, notes, or meetings, this unique, unstructured data can be invaluable to an investor. When used correctly, data can be the difference between closing a deal and missing a prime opportunity.
Below are three of the common challenges faced by investors.
Outdated systems
By the very nature of the industry, VCs have a tendency to keep pace with technological advancements. But while their portfolios may be brimming with AI solutions and high-tech software and services, not all VCs have implemented these innovations in their own business.
Outdated systems can create inefficiencies in processes and workflows. Relying on spreadsheets, email, and manual note-taking to manage deals, track investments, and analyze performance can lead to data silos and human error that can make it difficult to understand impact and scale operations.
Traditional systems are also behind the times when it comes to analyzing and generating insights from large data sets. This can make it hard for VCs to spot emerging trends and patterns that could help them better assess new opportunities. A lack of advanced analytics tools can leave VCs without critical insights that drive better decision-making.
When manually tracking hundreds or even thousands of potential deals, meeting notes, and investment criteria, it’s unsurprising that things get missed, including potential investment opportunities. But with the right tools and systems in place, investors can save time and secure more opportunities.
The broken relationship infrastructure
Venture capitalists are in the business of building relationships with entrepreneurs, limited partners, and other key stakeholders. For investors to be successful, there needs to be an infrastructure created to support these relationships within the VC firm. If the relationship infrastructure is fragmented, it can lead to suboptimal deal sourcing, portfolio management, and fundraising.
When different teams or individuals are communicating with the same contacts, communication can become siloed and disjointed. For example, if a team doesn’t have access to all relationship data, they may not know that an introduction between Portfolio Company A and Partner B could be beneficial for both parties. Siloed data can impede visibility and access to data across your team, which can cause firms to leave important insights and opportunities for collaboration on the table.
Without a strong system to manage relationships and share network connections, VCs may miss opportunities to cross-pollinate. While implementing new systems to connect data across firms is a financial investment, the resulting connections and opportunities uncovered are well worth the initial cost.
The silent crisis in data
Venture capital continues to be a data-driven industry year-over-year, but what if it’s all noise and no signal?
In the modern data landscape, VCs have access to massive amounts of information. From performance metrics, investor feedback, and market trends to past deal performance, relationship logs, and contact information, investors are inundated with data.
Having endless spreadsheets of financial projections or an inbox full of network interactions is great, but collecting data is only half the battle. If your data isn’t saying anything, it’s not helping you.
For example, a VC firm might have:
- Metrics on their portfolio companies’ growth, customer acquisition cost, churn rates, etc.
- Market data on trends, competition, and emerging technologies.
- Relationship data on past interactions, last point of contact, etc.
- Deal flow data like the number of startups assessed per year, how long it takes them to move through the pipeline, win rates, etc.
But all this data is sitting unused across spreadsheets, email chains, CRM systems, and even handwritten notes. Without a way to organize and analyze the data through the lens of the firm’s VC investment strategy, it can be hard to know how to make decisions based on it.
To track, organize, analyze, and draw actionable insights to drive decision-making from your data, you need the right tools. VC firms should be using a CRM system to track interactions with startups, investors, and other firms. But not all CRMs are created equal—VC funds need more than a traditional, sales-focused CRM that simply stores data. A CRM for VCs should:
- Integrate with other trusted third-party data sources to pull market data, financial reports, and firmographic, biographic, and funding data.
- Automate data entry to reduce the time investors spend manually entering data.
- Provide insights and recommendations to uncover key trends, high-potential deals, and highlight portfolio companies that may need attention.
How VCs are effectively using artificial intelligence
With the majority of VCs using AI in 2025, we continue to see new and novel ways investors are adopting artificial intelligence to improve firm operations. From deal sourcing to due diligence, here’s how VCs are using AI in their day-to-day operations.
1. Deal sourcing
Investors spend a lot of their time sourcing deals in order to find the hidden gems. VCs are no longer waiting for the perfect deal to fall into their lap—they’re going out and finding the deals for themselves. But when you’re sourcing and analyzing thousands of potential deals per year, time becomes a constraint to finding the best deals.
Marc Andreessen, founding partner of VC firm Andreessen Horowitz, says that they evaluate approximately 3,000 startups per year which breaks down to 12 opportunities per day (assuming a 5 days per week, 50 weeks per year schedule). Juggling the analysis of countless deals alongside the rest of a seemingly endless to-do list can quickly become an overwhelming challenge.
With the help of AI, you can shorten the time it takes to source potential deals before moving into the due diligence phase. Affinity’s Industry Insights gives you access to our proprietary data covering thousands of private and public companies. Using AI, Industry Insights provides a list of companies that match the target investment you’re assessing in the sourcing stage. The list includes companies that truly compete with the company you’re analyzing, giving you the information you need to help decide if a deal fits your fund’s investment thesis. Industry Insights is designed to shorten the amount of time investors spend in the early stage of deal assessments.
2. Due diligence
Because VCs invest more in seed, startup, or early stage companies, they tend to have less substantial evidence to demonstrate their value. Thorough due diligence to assess every available aspect of the company and its founders is essential to ensure a venture capital investment has a high likelihood of success.
According to a survey conducted by Harvard Business Review, VC firms report spending an average of 118 hours on due diligence per opportunity. Finding ways to reduce that time commitment without reducing the quality of work done during the due diligence process can help improve efficiency when closing deals.
Deal assist is a conversational interface that lets you ask questions and provides answers based on your notes, transcripts, research, and attachments. You no longer have to search through your deal data to find a specific answer. Instead, you can simply ask Deal Assist and it will find the answer to your question in your documents. With Deal Assist, you can finish due diligence faster with the power of artificial intelligence.
3. Daily task automation
Automating daily tasks is currently one of the most important uses of AI in VC firms—76% of firms use AI to automate tasks and increase productivity. Whether it’s automating notetaking during meetings, data entry, or pitch deck analysis, AI can help unburden investors from the important, but often mundane, daily tasks.
If manual data entry is causing errors like missed data or is taking up too much of your time, Affinity’s activity capture is the solution. Activity capture syncs with your email and meeting calendar, creating records based on communication activity. Your CRM records are automatically updated so you can capture data consistently and continuously. And the time normally spent on data entry can be reallocated to more important dealmaking activities. On average, Affinity customers save 200+ hours per year, per user on manual data entry that can be spent on other initiatives.
From introductory meetings with startups to diligence and partner meetings, investors find themselves in a lot of meetings each week. Often, VCs have to serve two separate functions during meetings—as an active listener and participant in the conversation and a thorough note-taker who’s diligently saving insights for future review. To make meetings more efficient, we created Affinity Notetaker, the perfect companion for all your meetings.
The tool joins you in your virtual meetings to create error-free, concise meeting notes and next steps so you don’t have to. It then automatically emails you the summary and adds the summary to your Affinity CRM. Relationship data is automatically enriched thanks to the information gathered during your meetings. Unlike other notetakers, Affinity Notetaker was created using our extensive knowledge of private capital. This ensures all summaries focus on what matters most to you as a dealmaker.
4. Relationship intelligence
VCs receive countless emails, messages, and event invites every day, and each interaction holds valuable information about a firm’s professional network. Known as relationship intelligence data, analyzing it can provide investors with valuable insights about their network that can be used to identify new opportunities, nurture important relationships, and drive productivity in your firm.
Affinity uses AI-driven algorithms to capture, analyze and enrich data to develop relationship insights. Coupled with activity capture and our AI features, Affinity provides users with a comprehensive database of contacts, engagements, shared connections, and more. By analyzing and using relationship insights, VC firms can uncover warn introductions, be notified when a key account needs attention, and find a pathway through their networks to close important deals faster.
Unlock efficiency with AI and Affinity
As the volume of data that venture capitalists consume continues to grow, AI is playing an important role in helping investors streamline workflows, uncover valuable insights, and maintain strong relationships. In the competitive landscape of private capital, firms who are early adopters of the latest AI advancements will have a distinct advantage over their competitors.
Affinity was—and is—purpose-built for private capital dealmakers. With network, deal, and portfolio data integrated across systems, Affinity allows VCs to understand every relationship in their firm’s network to drive deals and make decisions faster.
AI-driven tools like Deal Assist and Industry Insights help you tap into the venture capital market in ways that generic AI tools can’t. Designed for VCs, Affinity keeps you ahead of the curve by improving productivity, enhancing deal flow, and strengthening your network.
Transform how your firm works—speak to our team about how Affinity can improve your VC operations.
AI in venture capital FAQs
Which firms are investing the most in AI?
Based on PitchBook’s ranking of VC investors, the five firms that are investing in generative AI includes Sequoia Capital, Andreessen Horowitz (a16z), Pioneer Fund, Soma Capital, and Khosla Ventures.
How is AI used in venture capital?
Based on a survey of almost 300 dealmakers, VC firms are using AI to accelerate researching companies of interest, automate daily tasks, improve deal sourcing and due diligence processes, and create custom, personalized outreach.
How to use AI for VC?
Venture capital firms use AI to improve operations. VCs are using AI technologies and tools like Affinity, ChatGPT, and TechScout to increase operational efficiency, improve overall decision-making, and conduct real-time data analysis. Read our piece on the nine AI tools VCs are using in 2025 to learn how to build a tech stack supported by AI.
In which way will artificial intelligence change the way venture capital investors work?
AI-driven advancements will continue to reshape how all industries do business. As the technology matures, venture capital investors will benefit from new ways to use AI to improve their most important tasks—sourcing deals efficiently, managing the relationships in their networks, and improving deal management.
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