Top VCs Investing in AI — 2026 Guide

In our work advising 600+ startups, the most-active AI check writers cluster around Khosla Ventures, AI Fund, AIX Ventures, Conviction, and Gradient Ventures, with Andreessen Horowitz, Sequoia, Founders Fund, and Coatue dominating foundation-model rounds. Funding to foundational AI startups doubled in Q1 2026 vs all of 2025 — OpenAI, Anthropic, and xAI alone raised over $160B between them in the past 12 months.

If you're raising for an AI startup in 2026, the math has shifted. Foundational-AI funding doubled in Q1 2026 vs all of 2025 — and most of that capital is now concentrated in a handful of giants. The good news for everyone else: there's record-breaking dry powder for application-layer AI, vertical AI, and AI infrastructure plays.

We track active AI VCs in our Waveup Copilot database — the cards on this page sync from there weekly, so you're always pitching active funds, not last year's roster. Below is the working shortlist with focus, stage, check size, and live investment activity.

Best 5 AI VCs at a glance

1. Khosla Ventures — multi-stage generalist with deep AI portfolio (early OpenAI backer); $1M–$50M+ checks across seed through growth.
2. Conviction — Sarah Guo's AI-native fund; thesis-driven on application-layer AI; $1M–$10M Series A leads.
3. AIX Ventures — pure-play AI fund founded by Stanford AI researchers; seed and Series A.
4. Gradient Ventures — Google's AI fund; AI infrastructure + applied AI; pre-seed to Series A.
5. AI Fund — Andrew Ng's venture studio; pre-seed AI specialists; high-conviction operator backing.

Top venture capital firms investing in AI

AI VCs split into three patterns: foundation-model rounds ($1B+ at $10B+ valuations from a16z, Sequoia, Coatue, Founders Fund), application-layer Series A and B at $5M–$50M from Khosla / Conviction / AIX, and seed-stage AI specialists at $250K–$3M (Gradient, AI Fund, Hyperplane, Glasswing). The cards below sync with our database — focus areas, stage, and check sizes reflect each fund's current profile.

Methodology — how we keep this list current

We pulled this list from our Waveup Copilot fund database — VCs cross-checked against Crunchbase, TechCrunch, and the funds' own sites. To make the cut, a fund had to have an active AI thesis (not just incidental AI investments), be writing checks in 2024–2025, and cover at least one of pre-seed, seed, Series A, or growth.

Because the cards sync with our database, the focus areas, stage ranges, and check sizes you see reflect each fund's current mandate — not what we wrote when this article first published.

Foundation-model VCs (2026)

Andreessen Horowitz, Sequoia Capital, Founders Fund, Coatue, Iconiq Capital, Lightspeed Venture Partners, GIC, and the SoftBank Vision Fund dominate foundation-model rounds. These are $500M–$30B mega-rounds aimed at the 5–10 firms training frontier models. Most rounds now also include strategic capital from NVIDIA, Microsoft, Google, and Amazon — the line between VC and corporate strategic blurs at this scale.

The mega-rounds tell the story. OpenAI raised $40B Series F in April 2025 at a $300B valuation, then closed $110B in February 2026 at a $730B pre-money valuation — including $30B from SoftBank, $30B from NVIDIA, and $50B from Amazon. Anthropic's $13B Series F in September 2025 was followed by a $30B Series G in February 2026 led by GIC and Coatue at a $380B post-money valuation. xAI raised $20B Series E in early 2026, bringing total funding to $42.7B. France's Mistral raised $2B in September 2025 at $13.2B valuation, led by ASML.

Generative AI VCs

Conviction, AIX Ventures, Khosla Ventures, Gradient Ventures, Lightspeed Venture Partners, and Andreessen Horowitz lead generative-AI investing at the application layer. Generative AI took an outsized share of US VC in 2025 — application-layer companies like Cursor ($9.9B valuation), Glean ($7.2B), and Hebbia ($700M post-money) closed back-to-back rounds at premium multiples.

Application-layer GenAI is where most founders should actually pitch. Notable 2025–2026 rounds: Cursor (AI code editor) closed Series C at $9.9B valuation, Glean raised Series F at $7.2B valuation, and Hebbia AI closed $130M Series B led by Andreessen Horowitz at a $700M post-money. The pattern: application-layer plays with proprietary data + sharp ICP definition can still close fast at premium multiples in 2026, even as foundation-model rounds suck up most of the headline capital.

Seed-stage AI VCs

AI Fund, AIX Ventures, Gradient Ventures, Conviction, Hyperplane Venture Capital, Glasswing Ventures, BootstrapLabs, and Basis Set Ventures lead AI pre-seed and seed. Most write $250K–$3M checks and require either a working prototype, a credible technical wedge, or named-research-lab credentials. With foundation-model rounds taking the headline capital, seed AI specialists have repositioned around vertical AI, AI infrastructure, and applied ML rather than competing for frontier-model bets.

Enterprise AI / B2B AI VCs

Insight Partners, Bessemer Venture Partners, Battery Ventures, Sapphire Ventures, Iconiq, Menlo Ventures, and Boldstart Ventures lead enterprise / B2B AI. These funds focus on AI-native SaaS, vertical AI for legal/healthcare/finance, and AI infrastructure plays (data orchestration, model fine-tuning, observability). Check sizes range from $5M Series A leads to $50M+ growth rounds. Many founders raise here after they've shipped with at least 3–5 named enterprise pilot customers.

Why is AI still the biggest VC bet in 2026?

Funding to foundational AI startups doubled in Q1 2026 vs all of 2025. AI now takes about 35% of NYC VC, 30% of UK VC, and a similar share of Bay Area capital — the largest single sector concentration in venture history. Add proprietary-data moats, AI-native consumer apps with viral coefficients, and the enterprise AI replacement cycle, and AI keeps winning capital allocation against fintech, biotech, and climate.

The AI capital story isn't slowing — it's compounding. Crunchbase reports foundational-AI funding in Q1 2026 alone exceeded all of 2025, with capital increasingly concentrated in OpenAI, Anthropic, xAI, and Mistral at the foundation-model layer. AI now takes 35% of NYC VC, 30% of UK VC, and a similar share of Bay Area capital — the largest single sector concentration in venture history.

Two structural advantages keep AI on top in 2026. First, the proprietary-data moat — AI products that own a unique training dataset (medical records, legal contracts, financial transactions) compound their lead with every new customer. Second, the enterprise replacement cycle — Fortune 500 companies are rebuilding workflows around AI agents, which translates to real, recurring contracts at $100K–$10M+ annual values. The losers in this cycle: undifferentiated wrappers around frontier APIs and consumer DTC plays without strong viral coefficients.

But where opportunities show up, so does competition. Foundation-model rounds are now closed-shop deals. Application-layer plays need both proprietary data AND a sharp ICP wedge. Seed-stage AI is still gettable — but not for "yet another LLM wrapper." The bar is sharply higher than it was in 2024.

Related read:

• How to raise money for an AI startup
• Stealth startups: when to go stealth
• Top fintech VC firms
• Top B2B SaaS VC firms
• Top deep tech VC firms
• Top VC firms in San Francisco Bay Area & Silicon Valley
• Top venture capital firms in NYC
• Top venture capital firms in London

How should you pitch AI VCs in 2026?

We've seen founders close 70% faster when they lead with proprietary-data moat or a sharp vertical wedge — AI VCs in 2026 are pattern-matching against Cursor, Glean, and Hebbia, not against undifferentiated GPT wrappers. Build a 12–14-slide pitch deck, benchmark numbers against actual 2025–2026 AI deal data, and route the first intro through a portfolio founder, lab affiliation, or operator-angel.

AI is the single most competitive VC category right now — but also the deepest in capital. To stand out you need three things: deliberate target selection (the cards above tell you who actually writes checks for your stage and AI sub-niche), a deck that reads as technically rigorous (proprietary data, working model, real ICP), and a warm-intro path that bypasses the cold-pitch flood every AI partner now sees daily.

If you're not sure how to position your AI startup against Cursor/Glean-tier benchmarks — or whether your raise size and stage match the fund — our team has helped 600+ startups raise across AI, SaaS, fintech, and biotech. We'll tell you straight whether you're ready or what to fix first.