The Real Value of AI in VC? Time to Think.

August 6, 2025

By The Artemis Fund
The Artemis Fund believes technology can create prosperity for all. With offices in New York, Texas, Massachusetts, and Nevada, Artemis leads seed rounds for companies creating resilient families, individuals, and businesses across the US.
How are VCs actually using AI today? One fund told us AI cut their LP reporting time by 60%. Another built a custom agent to parse 1,200 LPs from public filings.
We envision a future where AI enables investors to spend less time on busywork and more time on decision-making and thesis development. While AI is adding early value, most of us are still in exploration mode. At Artemis, we believe early experimentation now will help us unlock outsized returns as these tools continue to improve.
We recently surveyed our peers on how AI is showing up in their workflows, and we’re excited to share how others are finding value in four main areas: writing assistance, research & diligence, deal flow, and internal leverage.

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Writing Assistance
Writing is one of the most effective and widely adopted use cases for AI in VC, particularly in content creation and LP reporting.
Content Creation
AI has dramatically sped up the path from brainstorm to publish:
Tools like ChatGPT, Perplexity, Gemini, and Notebook LM are now standard across fund workflows
Most funds (including ours) use the sandwich method: Human → AI → Human: start with a rough draft, refine with AI, and finish with human edits
Other insights from our network:
Lex is a standout tool for collaborative drafting
Teams are repurposing internal memos into fast, shareable “Why We Invested” content
Custom GPTs can be trained to match voice and tone for consistency across communications.
💡Tip: Read Artemis’ writeup on how to create a custom GPT for content strategy here.
Reporting
LP updates are critical for transparency and relationship building. They’re also a great use case for AI’s ability to take lots of data and streamline it down:
Custom GPTs trained on prior reports are reducing time by up to 60%
Notebook LM and Gemini integrate with Google Drive to auto-pull data from portfolio company materials
New platforms like TotemVC are embedding summarization directly into fund CRMs
💡Tip: Always double check AI-generated reports and limit the use of sensitive inputs, even in secure tools. Data quality & security should be top priority.
Research & Diligence
AI isn’t replacing investor judgment, but it’s making it faster to form an opinion. When used well, AI tools can accelerate research, expand surface area, and spotlight patterns.
Market Research
AI helps investors get smart, fast. While these tools save hours, the best results still require thoughtful prompting and human validation.
Tools like Wokelo can generate detailed, 30–40 page industry reports in under an hour
ChatGPT and Perplexity are widely used for market sizing, benchmarking, and discovery work
Importantly, conversations with customers and experts haven’t gone away; AI prepares you to ask better questions, but it doesn’t ask them for you.
Pipeline Intelligence
Deal teams are increasingly using AI to mine their historical data for insights.
Granola lets teams query past meeting notes, transcripts, and calls to answer questions like, “which company had this traction signal?”
Tools like Zams, DoubleO, and Concierge enable teams to build lightweight agents that parse emails, decks, and internal docs
AI is unlocking leverage in diligence by turning messy, fragmented data into something usable.
Deal Flow
AI is starting to reshape how VCs manage sourcing, screening, and networks, but these processes are still largely manual. 
Here are the areas where the most forward-leaning funds are experimenting:
Network Management
A new generation of tools is helping VCs tap into their networks more creatively than ever before:
Paly: YC-backed platform for managing contacts across multiple systems
Happenstance: People-search engine that reveals latent network connections
Goodword: Relationship copilot that surfaces warm intros and strategic touchpoints
Sourcing
AI is expanding what’s possible in proactive discovery:
Specter and Harmonic are layering AI insights on top of traditional databases
Some investors are scraping SEC filings or using AI to spot stealth founders before launch
Outbound messages
AI-driven outreach remains a work in progress:
Octopus automates LinkedIn messages using templates and scheduling
A few firms are testing ChatGPT-based agents to draft personalized messages or map warm intro paths
Overall, most early-stage founders expect a human touch, and automated outreach often falls flat.
Screening
AI tools are helping funds sort through the inbound flood faster:
Fyva AI scores opportunities based on criteria like team strength, market size, and competition
Crew builds internal agents that scan startup websites and application materials, integrating directly with tools like Airtable for seamless triage
Internal Leverage
From our perspective, one of the most exciting use cases is automating repetitive internal tasks.
Data Capture
Frictionless documentation and surfacing insights is one of AI’s most tangible contributions to fund operations:
Wispr Flow allows seamless dictation in any app, a surprisingly useful tool for capturing thoughts on the go
Affinity AI Insights summarizes email threads and documents inside the CRM
Obsidian combines note-taking, project tracking, and personal knowledge management in one customizable platform
AI wearables, like pendants or smart glasses, that transcribe and summarize meetings in real-time are showing up more frequently
Emerging Ops Use Cases
Firms are also experimenting with lightweight agents and AI workflows for internal leverage:
Legal Triage: ChatGPT is being used for first-pass contract reviews to flag risks before legal counsel steps in
Website FAQs: Some funds are exploring tools like Delphi AI for handling inbound site queries
Weekly Planning: One team is combining calendar screenshots and transcripts to generate task lists via AI
IC Summaries: Internal investment meetings are being transcribed and summarized automatically for better decision tracking
LP Discovery: A Replit-based agent helped one firm scrape and structure 1,200 LP contacts from public fund announcements
Most early-stage investors remain cautious about relying too heavily on AI. Personalization in early-stage outreach still requires a human touch, and AI’s judgment on investability lacks the depth that comes from real founder interaction. At its best, AI enhances (not replaces) what makes early-stage venture work: curiosity, conviction, and human connection.
Thank you to everyone who chatted with us about their workflows: Eastin Russel at Hearst, Mirit Lugassi at Laconia, Maria Heyen at Redbud, Yohei Nakajima at Untapped Capital, Ariella Frank at New Stack, Marina Girgis at Precursor, Bailie Salk at Venrock, Gale Wilkinson at Vitalize, Brian Gong at Cameron Ventures, Peri Ehlman at Chingona, Kat McGuire at Trust Ventures, and several others!
We believe once in a generation companies will be built by unexpected founders. If that sounds like you, pitch us here!

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