PitchBook年一季度人工智能和机器学习风险投资趋势(英)
EMERGING TECH RESEARCHAI & ML VC TrendsVC activity across the AI & ML ecosystemQ12025REPORT PREVIEWThe full report is available through the PitchBook Platform.CONFIDENTIAL. NOT FOR REDISTRIBUTION. PG 2ContentsQ1 2025 AI & ML VC TrendsInstitutional Research GroupAnalysisDimitri Zabelin Senior Research Analyst, AI/ML & Cybersecurity dimitri.zabelin@pitchbook.comDataMatthew Nacionales Senior Data Analystpbinstitutionalresearch@pitchbook.comPublishingReport designed by Chloe Ladwig, Julia Midkiff, and Drew SandersPublished on July 8, 2025AI & ML landscape 3AI & ML VC ecosystem market map 4VC activity 5AI & ML VC deal summary 15AI & ML VC deal summary 16CONFIDENTIAL. NOT FOR REDISTRIBUTION. PG 3Q1 2025 AI & ML VC TrendsAI & ML landscapeHorizontal platformsVertical applicationsSemiconductorsAutonomous machinesCONFIDENTIAL. NOT FOR REDISTRIBUTION. PG 4Q1 2025 AI & ML VC TrendsAI & ML VC ecosystem market mapCONFIDENTIAL. NOT FOR REDISTRIBUTION. PG 5Q1 2025 AI & ML VC TrendsVC activityAI captured one in every four VC dollars globally in 2024, a trend likely to accelerate as adoption deepens and infrastructure scales. Capital continues to flow into both horizontal platforms such as OpenAI and Anthropic and sector-specific vertical applications built on top of them. Falling development costs at the application layer are fueling record deal volume even as funding remains concentrated at the top. This report breaks down the split between platform and application layers, recent exit activity, and shifting valuation dynamicsAI and machine learning (ML) startups raised a record-breaking $73.6 billion across 1,603 deals in Q1 2025, marking the highest quarterly total on record by deal value. Deal counts were at their highest level since Q1 2024. Horizontal AI platforms captured the lion’s share, securing just under $50 billion across 425 deals, accounting for nearly 70% of total capital raised during the quarter. Horizontal platforms are general-purpose tools, such as large language models and infrastructures that support a wide range of industriesIn contrast, vertical application startups led in deal volume, notching 1,022 transactions, roughly 60% of all deals, with an aggregate deal value of $19.2 billion. Vertical applications are tailored to specific sectors and built on top of horizontal platforms, which enable domain-specific performance and integration.The stark contrast between capital raised and deal count reflects underlying cost dynamics. Vertical models can be developed with just $3 million to $10 million in funding, while horizontal large language model (LLM) development can cost hundreds of millions of dollars at the high end. This cost differential has lowered the barrier to entry at the application layer, where most AI startups are building on existing horizontal platforms. Another driving force behind the surge in vertical deals is the opportunity for startups to develop specific solutions with commercial value to large enterprises acros
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