3 VCs and 2 funds investing in AI infrastructure
General Partner
Andreessen Horowitz (a16z)
Check: $1M-$100M+ (from a16z's $5.2B AI fund, largest sector allocation in 2026)
Leads a16z's AI investments from the $5.2B AI allocation — the firm's largest sector bet ever. Anjney came to AI from an unusual path: he previously led a16z's crypto gaming investments, giving him deep understanding of platform transitions, virtual economies, and consumer behavior in digital worlds. His AI thesis is built on the belief that AI is a platform shift as significant as mobile or cloud — and that the biggest opportunities are at both the infrastructure layer (foundation models, training, inference) and the application layer (consumer AI, AI agents, vertical applications). Particularly bullish on consumer AI as a social phenomenon — Character.ai embodies this, where AI characters become companions and social interactions, not just tools. Believes open-weight models (Mistral, Meta's Llama) will create an ecosystem similar to open-source software, where the most innovative applications are built on open foundations. Views gaming as a leading indicator for AI adoption — games were the first consumer products to adopt AI-generated content, AI NPCs, and AI-powered user experiences.
General Partner
Andreessen Horowitz (a16z)
Check: $1M-$100M+ (leads a16z's $1.25B+ infrastructure fund)
Leads a16z's infrastructure practice and is one of Silicon Valley's most technically credible VCs, having built VMware NSX and pioneered software-defined networking. Invests 'from markets in' rather than 'from companies out' — he maps massive market opportunities first, then finds founders who can serve them. Believes AI is analogous to 1996 of the internet boom with years of growth still ahead. Sees the AI coding market alone as a potential $3 trillion opportunity. Vocal advocate for open source in AI — co-authored a piece in The Economist with Ion Stoica arguing open source is critical to AI's future. Deeply concerned about Chinese dominance in open-source AI models (claims ~80% of his portfolio companies use Chinese open-source models). Thinks AI value will ultimately accrue at the application layer more than the model layer, drawing parallels to how SaaS-era startups captured more value at the application layer than infrastructure. Believes AI is fundamentally changing SaaS pricing from per-seat to outcome-based models. Champions spatial intelligence as AI's next frontier (deeply involved with World Labs / Fei-Fei Li).
Partner
Sequoia Capital
Check: $500K-$50M+ (stage dependent)
The defining voice of Sequoia's AI thesis and arguably the most influential AI investor-thinker in Silicon Valley. Co-authors a series of landmark essays with Pat Grady that have become the canonical frameworks for understanding generative AI's evolution. Core conviction: the application layer — not foundation models — is where enduring value accrues. Foundation models are commoditizing rapidly (only five scaled players remain: Microsoft/OpenAI, Amazon/Anthropic, Google, Meta, xAI), so the real opportunity is in vertical AI applications that solve end-to-end human problems. Believes we have entered the 'Age of Abundance' where AI makes once-scarce labor available everywhere at near-zero cost, transforming the addressable market from software ($1T) to services ($10T+). In this world, 'taste' — the human judgment to decide what to build and how — becomes the scarcest resource. Her January 2026 essay declares AGI is functionally here in the form of long-horizon agents that can sustain multi-step work, correct errors, and persist toward goals autonomously. Sequoia has deployed roughly $150M into foundation models but over $1.5B into application-layer companies, reflecting a 10:1 bet on applications over infrastructure.