Venture Capital Intelligence Report
April 20, 2026 • Synthesizing insights from top-tier VCs
VCs are seeing strong fundamentals in AI/enterprise but becoming more selective after 2023-2024 froth. Public market recovery signals renewed confidence but valuations still correcting from peak levels.
Series A crunch continues with 60% fewer deals but larger sizes. Seed remains active for AI/infra. Growth stage highly selective - profitability path required.
Down 30-40% from 2021 peaks but stabilizing. AI companies command premium but must show clear moats. SaaS multiples compressed to 6-8x ARR for growth cos.
Foundation model training infrastructure and inference optimization still early innings. Enterprise deployment needs specialized tooling.
Moving beyond chatbots to autonomous agents that can complete multi-step workflows in specific industries.
Institutional adoption driving need for enterprise-grade custody, compliance, and analytics tools. RWA tokenization gaining traction.
Beyond mitigation to adaptation - helping companies and cities prepare for climate impacts already locked in.
Geopolitical tensions and AI arms race driving defense spending. Dual-use tech with commercial applications preferred.
AI infrastructure spend will reach $1T by 2030, but most value will accrue to specialized middleware companies, not just compute providers.
Companies adopting AI agents early will have 10x productivity advantages within 18 months. This is not about replacing humans but augmenting workflows.
Usage-based pricing models will replace traditional SaaS subscriptions as AI makes software more outcome-driven.
As climate mitigation efforts lag, adaptation tech becomes essential. Insurance, agriculture, and urban planning will drive $500B market.
European regulations (AI Act) will create protected market for EU-based AI companies, similar to how GDPR created EU privacy tech market.
Security tools built from ground up to protect AI systems and AI-powered companies from new attack vectors.
AI adoption creating new vulnerabilities - prompt injection, model poisoning, data poisoning attacks becoming common.
$50B+ market as every AI company needs specialized security
Early signals from: Accel, General Catalyst
Companies to watch: Robust Intelligence, HiddenLayer, Protect AI
AI agents that can orchestrate complex multi-step business processes across systems without human intervention.
Foundation models now capable enough to handle multi-step reasoning and tool use reliably.
$200B+ RPA market being rebuilt with AI agents
Early signals from: Greylock, Bessemer
Companies to watch: Zapier Central, Multion, Adept
Backend infrastructure and dev tools for AR/VR applications as Apple Vision Pro creates new category.
Apple Vision Pro proving market exists, but developers need better tools and infrastructure.
$30B+ as spatial computing goes mainstream
Early signals from: a16z, Lightspeed
Companies to watch: 8th Wall, Niantic, Magic Leap
Corporate wellness and longevity programs as companies realize health is their biggest cost after talent.
Aging workforce and healthcare costs making prevention economically attractive to employers.
$100B+ corporate wellness market being upgraded with longevity science
Early signals from: Founders Fund, GV
Companies to watch: Fountain Life, Levels, Function Health
Previous: Red hot during 2020-2022 → Now: Significantly cooled
User acquisition costs skyrocketed, monetization challenges, and market saturation. TikTok dominance hard to challenge.
What Changed: iOS privacy changes, economic downturn reduced brand spending, and consolidation around established platforms
VCs Cautious: Benchmark, Accel, Lightspeed
Previous: Extremely hot in 2021-2022 → Now: Largely abandoned
Speculation bubble burst, poor user experience, and lack of sustainable game mechanics.
What Changed: Market realized token gating doesn't create sustainable gaming experiences
VCs Cautious: Most except specialized crypto VCs
Previous: Very hot pre-2022 → Now: Selective interest only
Customer acquisition costs unsustainable, difficult to defend against Amazon, and capital intensive.
What Changed: Post-pandemic normalization exposed weak unit economics for many DTC brands
VCs Cautious: General Catalyst, Forerunner, First Round
Data moats are temporary. Focus on workflow integration and outcome guarantees as sustainable differentiation.
💡 Build irreplaceable workflows, not just better models. Own the customer relationship and business outcome.
— Sequoia Capital
CFOs now have AI budget line items. Lead with ROI metrics and automation savings, not technology features.
💡 Create ROI calculators showing exact cost savings. Pilot programs should demonstrate measurable productivity gains.
— Bessemer Venture Partners
AI engineers are the new mobile developers. Recruit from research labs and offer equity-heavy packages.
💡 Partner with universities, offer research sabbaticals, and compete on learning opportunities, not just compensation.
— Index Ventures
Demonstrate clear path to profitability by Series B. Growth-at-all-costs is dead - unit economics matter from day one.
💡 Build financial models showing break-even timeline. Focus on sustainable growth metrics, not just top-line growth.
— General Catalyst
Product-led growth works for AI tools, but enterprise requires human-assisted onboarding to drive adoption.
💡 Hybrid PLG model - easy to try, but invest in customer success to drive expansion and retention.
— Greylock Partners
Deal activity up 25% QoQ but still down 40% YoY. Quality deals getting done at reasonable valuations. Series A median down to $8M from $12M peak.
Series C • Lead: Google • Others: Spark Capital, Salesforce Ventures
Largest AI round ever, validates massive capital requirements for foundation model competition
Foundation ModelsSeries I • Lead: T. Rowe Price • Others: Andreessen Horowitz, NEA
AI data infrastructure command premium valuations as enterprises rebuild data stack
Data InfrastructureSeries E • Lead: Accel • Others: Tiger Global, Dragoneer
Data quality becoming bottleneck for AI adoption - Scale positioning as infrastructure layer
AI Data ServicesAcquisition • Key investors: Accel, CapitalG, Sequoia
Traditional RPA still valuable but needs AI integration to compete with newer solutions
Strong Public Performance • Key investors: Sutter Hill, Redpoint
Data infrastructure companies with AI integration seeing massive re-ratings in public markets
Most AI startups will fail because they're building features, not products
AI is transformative and will create massive value
Reasoning: Historical pattern - new technology creates many experiments but few sustainable businesses. Need distribution and business model innovation, not just technology.
Their Bet: Investing in AI-enabled vertical software companies with proven business models rather than pure-play AI companies