---
title: How VC firms use AI, and what stays private
description: How venture firms use AI for sourcing, memos, portfolio monitoring and LP updates in 2026, from survey data, and what each use exposes of founder and LP data.
canonical: https://privatesuperintelligence.si/blog/how-vc-firms-use-ai/
last-updated: 2026-10-15
---

# How VC firms use AI, and what stays private

Most venture capital firms now use AI for internal work, and far fewer use it where LP data sits. Visible's 2026 AI Sentiment Report found that 57% of VC firms use AI in internal operations, while 16% use it for LP reporting, and security concerns (51%) are the barrier firms name most. The pattern makes sense once you map each use to the data it touches: founder decks, the CRM, portfolio financials and LP records carry different obligations.

## What the survey numbers say

Visible, which makes portfolio monitoring software for investors, published the report in 2026. It does not publish its sample size or survey dates on the report page, so read the figures as a snapshot of firms in its orbit, not the whole industry.

| Finding (Visible, AI Sentiment Report Vol. 1) | Share of firms |
|---|---|
| Use AI in internal operations | 57% |
| Use AI for LP reporting | 16% |
| Use AI to identify trends across portfolio data | 16% |
| Use AI to benchmark portfolio performance | 8% |
| Highly confident AI will transform firm operations within 12 months | 81% |
| Adopted zero new AI tools in the past 90 days | 30% |
| Built zero new AI workflows in the same period | 40% |

The blockers firms named were security concerns (51%), tool overload (49%), data quality (41%) and unclear ROI (16%). Visible also reports that its average customer extracted 10 times more portfolio metrics with AI than the year before, and that its AI Inbox went from 10% to over 40% of all metrics collected.

So partners expect a lot from AI, and a large minority added nothing new in a quarter. Lisa Cawley, Managing Director at Screen Door, put one version of that stance in the report: "I actually don't believe in adopting every single net new AI tool out there the second it comes out."

## Where AI shows up across a venture fund

ILPA's Due Diligence Questionnaire (DDQ 2.0) asks a firm to list the technology tool it uses for each business function, from deal sourcing and screening through due diligence, portfolio monitoring and reporting to investor relations. That list is a useful map of where AI now lands, and of the data each job touches.

| Work | What AI does today | Data it touches |
|---|---|---|
| Sourcing and deal flow | Searches company databases, flags hiring and fundraising signals, summarizes inbound decks | Public data, plus the partners' inboxes and calendar if you sync them |
| Screening and diligence | Reads a data room, pulls out metrics, drafts questions for the founder | Founder financials, cap tables and contracts, often shared under NDA |
| IC memos | Produces a first-draft deal memo from the deck, call notes and the data room | Everything above, plus the partners' own views |
| Portfolio monitoring | Extracts KPIs from founder updates and board decks | Portfolio companies' non-public results |
| LP reporting and IR | Drafts quarterly letters, answers DDQs and LP questions | LP identities, commitments, capital accounts, side letter terms |
| Fund operations | Summarizes LPAs, tracks capital calls, drafts routine email | Fund documents and LP banking details |

The rows near the top start from public information. The rows near the bottom are almost all confidential, which helps explain why internal use sits at 57% and LP reporting at 16%.

## What each use exposes

Two kinds of data sit behind most of these jobs, and they belong to other people.

**Founder data.** A founder sends a deck, a model and a cap table so you can decide on an investment. If you signed an NDA, the template may well predate generative AI. DarrowEverett, a law firm, wrote in June 2026 that most NDAs limit disclosure to "third parties" or a defined purpose, and that putting deal information into an AI tool may breach an NDA "even if an NDA is silent on AI," because the information leaves the permitted circle and becomes subject to the AI company's terms.

**LP data.** Your LPA and side letters set the confidentiality terms for LP names, commitments and side letter provisions, so read them before any of it goes into an AI tool. LPs also ask about your controls: section 18 of the ILPA DDQ asks whether firm data held by third-party providers gets security reviews and independent assessments, and whether sensitive data is encrypted at rest and in transit.

The AI plan you use decides part of the answer. OpenAI says ChatGPT Business, Enterprise and Edu do not train on workspace content by default, while Free, Go, Plus and Pro may use chats for training unless you turn off "Improve the model for everyone." Even after opting out, rating a response with a thumbs up or down can send that whole conversation for training. Our guide [Is ChatGPT safe for confidential information?](/blog/is-chatgpt-safe-for-confidential-information/) has the plan-by-plan table, and [ChatGPT for venture capital](/blog/chatgpt-for-venture-capital/) applies it to decks and NDAs.

## Why adoption lags the confidence

The three biggest blockers in Visible's survey point at different problems.

- **Security concerns (51%)** are about the data in the table above. A partner who can't say where a founder's model went won't paste it in.
- **Tool overload (49%)** is about the stack. A sourcing database, a CRM with AI agents, a document tool and a chat assistant each hold a slice of the firm's information, and each needs its own review.
- **Data quality (41%)** is about the inputs. If portfolio KPIs arrive in five formats, an AI summary of them inherits the mess.

Fixing the first blocker tends to make the other two worse if you solve it by adding one more single-purpose tool. One way out is fewer tools that reach more of the firm's information under one set of rules.

## What to set up first

If your firm is early, a short sequence covers most of the risk:

1. **Write down which data goes where.** Public research can go to any business-plan assistant. Founder materials and LP records need a tool your firm has reviewed.
2. **Move everyone off personal accounts.** Personal ChatGPT plans may train on chats by default. A business workspace does not.
3. **Check your NDAs and side letters** for confidentiality terms that cover third-party processing, and decide what you'll say when a founder asks.
4. **Prepare your DDQ answer.** List the AI tools you use by function, as ILPA's Appendix D template asks, and describe the controls on each.
5. **Require citations** for any figure an AI puts in a memo or an LP letter, so a person can check it against the source.

For a tool-by-tool view, read [AI tools for venture capital, and what each sees](/blog/best-ai-tools-for-venture-capital/). For diligence, read [AI due diligence for venture capital](/blog/ai-due-diligence-for-vc/).

## Private SuperIntelligence for venture firms

Private SuperIntelligence is the most capable AI, trusted with everything your firm knows. It works across the firm's own email, documents and data, answers with citations, and acts within permissions you set, with each deployment built for one firm. The provider keeps no copy of the work, trains nothing on it and cannot see the outputs. Read more on [AI for venture capital firms](/venture-capital/).

## Frequently asked questions

### How do VCs use AI?

Most use it for internal operations first: research, first-draft memos, meeting notes and email. Visible's 2026 survey found 57% of VC firms use AI in internal operations, 16% for LP reporting and 16% to spot trends across portfolio data.

### What stops VC firms from using more AI?

In Visible's survey, firms named security concerns (51%), tool overload (49%), data quality (41%) and unclear ROI (16%). Security matters most where founder and LP data are involved.

### Do LPs ask about a firm's AI use?

ILPA's DDQ 2.0, released in November 2021, has no question that names AI, but it asks you to list the technology tools you use for each function and to describe security reviews of data held by third parties. ILPA's Responsible AI Quick Guide (January 2024) suggests LPs ask what controls a GP has around AI use at the fund level.

### Is it safe to put a founder's pitch deck into an AI tool?

It depends on the plan and on what you agreed with the founder. Business plans of the major assistants don't train on your data by default, but a law firm analysis from June 2026 argues that sharing NDA material with any AI provider may count as disclosure to a third party. This is general information, not legal advice.

### Which AI uses are lowest risk for a VC firm?

Work that starts from public information, such as market maps, public company research and drafting from your own notes, carries the least exposure. Risk rises as you move toward founder financials and LP records.


## Related reading

- [ChatGPT for venture capital: decks, NDAs and LP data](/blog/chatgpt-for-venture-capital/)
- [AI due diligence for venture capital](/blog/ai-due-diligence-for-vc/)
- [AI for LP reporting and investor relations](/blog/ai-for-lp-reporting/)
- [AI tools for venture capital, and what each sees](/blog/best-ai-tools-for-venture-capital/)
- [Is ChatGPT safe for confidential information?](/blog/is-chatgpt-safe-for-confidential-information/)
- [What is zero data retention AI?](/blog/zero-data-retention-ai/)
- [What is private superintelligence?](/blog/what-is-private-superintelligence/)

## Sources

- [AI Sentiment Report Vol. 1 (Visible, 2026)](https://visible.vc/blog/ai-sentiment-report-v1/), accessed 2026-10-15
- [Due Diligence Questionnaire 2.0 (ILPA, November 2021)](https://ilpa.org/wp-content/uploads/2021/11/ILPA-DDQ-2.0.pdf)
- [Responsible AI Quick Guide for Asset Owners (ILPA, January 2024)](https://ilpa.org/wp-content/uploads/2023/10/Responsible-AI-Quick-Guide-for-Asset-Owners.pdf)
- [Loose Lips, Large Language Models: What Your NDA is Missing in the Age of AI (DarrowEverett LLP, June 2, 2026)](https://darroweverett.com/ndas-non-disclosure-agreements-age-ai-practical-steps-analysis/)
- [Data controls in ChatGPT (OpenAI Help Center)](https://help.openai.com/en/articles/7730893-data-controls-faq), accessed 2026-10-15
- [Enterprise privacy at OpenAI (OpenAI)](https://openai.com/enterprise-privacy/), accessed 2026-10-15