Venture Capital Intelligence Report
February 24, 2026 • Synthesizing insights from top-tier VCs
VCs are increasingly selective after 18 months of AI infrastructure buildout. Focus shifting from foundational models to application layer and vertical AI solutions with clear revenue models.
Correction continuing in growth stages. Seed/Series A remain active for AI and climate tech, but Series B+ require stronger unit economics. Median pre-money down 30-40% from 2021 peaks.
Reality-based pricing emerging. AI infrastructure still commands premiums but application layer valuations compressing. Revenue multiples normalizing to 8-12x for SaaS vs 15-25x in 2021.
The picks-and-shovels play remains strong as enterprises need better tools to deploy, monitor, and optimize AI workloads at scale
Industry-specific AI solutions with deep domain expertise showing stronger retention and expansion than horizontal tools
IRA funding and corporate climate commitments driving demand for measurement, carbon management, and clean energy infrastructure
AI-powered development tools showing 20-40% productivity gains, driving strong bottom-up adoption and enterprise expansion
Next-gen financial infrastructure leveraging AI for risk, compliance, and personalization as crypto integration normalizes
Traditional SaaS categories will be disrupted by AI agents that can perform end-to-end workflows rather than just providing interfaces
$4T+ services market (legal, accounting, consulting) ripe for software displacement through AI, not just augmentation
AI finally making climate tech scalable through better prediction, optimization, and automation of clean energy systems
FDA's new AI approval pathways and CMS reimbursement clarity creating investable healthcare AI opportunities
Security tools built from the ground up to protect AI systems, data, and prevent model abuse
Enterprise AI deployments creating new attack vectors that traditional security can't address
$50B+ market as AI security becomes compliance requirement
Early signals from: Sequoia, Lightspeed, Bessemer
Companies to watch: Robust Intelligence, HiddenLayer, Protect AI
Backend infrastructure and dev tools for AR/VR applications as Apple Vision Pro creates market
Vision Pro proving spatial computing demand; developers need tools to build experiences
$25B+ market if spatial computing achieves 10% of mobile app market
Early signals from: a16z, Benchmark, Index
Companies to watch: 8th Wall, Niantic, Magic Leap
AI systems that can formulate hypotheses, design experiments, and accelerate scientific discovery
Recent breakthroughs in protein folding and materials science proving AI can accelerate discovery
$100B+ across drug discovery, materials, and climate solutions
Early signals from: Kleiner, GV, NEA
Companies to watch: Recursion, DeepMind, Atomic AI
Previous: Red hot in 2021-2022 with TikTok competition focus → Now: Significantly cooled
User acquisition costs spiked, platform dependency risks, and regulatory uncertainty around data privacy
What Changed: iOS 14.5 attribution changes and TikTok ban uncertainty shifted VC appetite toward B2B
VCs Cautious: Benchmark, Lightspeed, General Catalyst
Previous: Massive hype in 2021-2022 with play-to-earn models → Now: Investment down 70% from peak
Most P2E models failed to achieve sustainable gameplay loops, regulatory uncertainty, and user adoption plateaued
What Changed: Focus shifted from token incentives to actual game quality and retention metrics
VCs Cautious: a16z, Paradigm, Coinbase Ventures
Previous: Peak pandemic darling sector → Now: Selective interest only
Customer acquisition costs unsustainable, supply chain issues, and return to offline shopping patterns
What Changed: iOS changes killed performance marketing arbitrage that fueled DTC growth
VCs Cautious: Forerunner, First Round, Lightspeed
Don't build your own LLM unless you have $100M+ and unique data advantage - focus on fine-tuning and application layer
💡 Use existing foundation models (OpenAI, Anthropic) and compete on data flywheel and user experience
— Sequoia Capital
CFOs now demanding AI ROI proof within 90 days - need clear metrics and quick wins before broader deployment
💡 Structure pilots with specific KPIs and measurement frameworks; don't sell 'AI transformation'
— Bessemer Venture Partners
AI talent costs peaked - focus on product engineers who can build with AI rather than AI researchers
💡 Hire for AI integration skills rather than ML PhD credentials; product-AI fit more valuable than model innovation
— Greylock Partners
EU AI Act compliance becoming competitive advantage - US companies that get ahead will win European deals
💡 Build privacy, explainability, and bias monitoring into your AI systems from day one
— Index Ventures
Deal volume down 35% YoY but average deal size up 15%. Quality over quantity trend continuing with VCs focusing on companies with clear paths to profitability.
Series C • Lead: Spark Capital • Others: Google, Salesforce Ventures
Largest AI round of 2026 - validates continued investment in model development despite commoditization fears
Foundation ModelsSeries B • Lead: Bessemer Venture Partners • Others: Nvidia, Microsoft
Robotics finally hitting commercial viability with AI integration - manufacturing applications driving growth
AI RoboticsAcquisition • Key investors: Bessemer, IVP, Insight Partners
Content AI consolidation continuing as enterprises prefer integrated suites over point solutions
IPO • Key investors: Index Ventures, Battery Ventures, Dawn Capital
Data governance becoming critical as AI deployments scale - regulatory compliance driving valuations
Open source AI will win over proprietary models
Most VCs betting on closed model providers like OpenAI/Anthropic
Reasoning: Developer preference for customization and cost control will drive open source adoption; commoditization favors infrastructure players
Their Bet: Leading rounds in Hugging Face and Together AI while avoiding foundation model companies
Europe will lead AI regulation compliance tools
US-centric AI investment focus
Reasoning: EU AI Act creating first-mover advantage for European AI governance companies; US companies will need to comply anyway
Their Bet: Doubling down on European AI governance and explainability startups
SMB AI adoption will outpace enterprise
Enterprise-first AI go-to-market strategies
Reasoning: SMBs have less legacy infrastructure and faster decision-making; consumer AI tools proving bottom-up adoption works
Their Bet: Investing in prosumer and SMB-focused AI tools rather than enterprise-only plays
First $100B AI company will emerge by end of 2026
MEDIUMAndreessen Horowitz • Timeframe: Q4 2026
Implications: Will validate AI as platform shift on par with mobile; drive massive increase in AI investment