These significant cash infusions signal where investors are placing the biggest bets at a given time and which startups are being positioned to shape or disrupt markets.

To track trends in mega-rounds, our monthly Book of Scouting Reports offers an in-depth analysis of every private company that has raised a funding round of $100M or more. The scouting reports provide insight into each company’s funding history and latest round; headcount; opportunities & threats; commercial maturity; and business health.

Download the book to see all 46 scouting reports.

Key trends from June’s mega-rounds include:

• AI attracts the largest funding rounds, fueled by tech talent wars: Meta invested a massive $14.8B in Scale, whose CEO is also joining the tech giant. Thinking Machines Lab raised $2B in seed funding without a live product, with several former OpenAI executives having joined the company. These rounds show how quickly AI talent is moving around the industry — and the hefty price tags that this talent can command.
• Industrials command a third of mega-rounds in June, indicating a hardware renaissance: Industrial companies (including defense, aerospace, energy, and robotics) drove many of this month’s $100M+ deals, from Anduril‘s $2.5B round to Helsing‘s nearly $700M deal. While AI is central to many of the companies in this sector, almost all are developing physical hardware and infrastructure. 
• Quantum computing players get a boost from AI and defense applications: Two quantum computing companies raised mega-rounds in June ’25: Infleqtion, which develops quantum sensing for defense, and AI 100 winner Multiverse Computing, which provides quantum-enabled model compression to speed up AI processing. While not a substantial share of deals, these investments point to an increased demand for quantum capabilities across high-growth applications.
• Capital is going toward product and R&D: 37% of mega-round recipients are directing these funds toward product development and core technology advancement, including AI. For example, Observe intends to use the capital to expand its AI observability features, while Impulse Space is planning R&D for new vehicles for NASA and defense customers. 

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So far this year, 53 companies have reached billion-dollar valuations, putting 2025 on pace to exceed the 80 unicorns minted in all of 2024.

Artificial intelligence is the key driver behind this surge, with AI startups accounting for over half of all new unicorns in 2025 so far. These AI-native unicorns are also breaking the mold, reaching $1B+ valuations on faster timelines, hitting the milestone in 6 years versus the typical 7.

Here’s what today’s unicorn landscape signals about the future of tech:

• 1 in 5 new unicorns are AI agents, with AI taking over the unicorn landscape, representing 53% of all new billion-dollar companies in 2025 so far. Among the newest unicorns, 12 are building AI agents, including Hippocratic AI (healthcare), Cyberhaven (data security), and Parloa (customer support). 
• Newer unicorns generate 83% more revenue per employee than older ones, with $814K per employee on average, compared to the $446K average across all unicorns. This reflects automation-first approaches and leaner operations that avoid the operational bloat older unicorns accumulated during their growth phases. For example, among unicorns born in 2025, the company with the highest revenue per employee is soft drink company Olipop ($1.2M/employee), followed by AI sales agent unicorn Clay ($1M/employee).
• Consumer and fintech companies are most primed to exit, boasting the highest M&A probability scores among the top Mosaic-scoring companies. While payments company PPRO tops the list with a 53% probability of getting acquired in the next 2 years, consumer & retail companies dominate the middle tier with ID.me (41%), Cart.com (33%), and Vestiaire Collective (31%), suggesting acquirers see solutions like identity verification, e-commerce infrastructure, and marketplace platforms as prime M&A targets.

CBI customers: Dive into data on every unicorn

Market map of billion-dollar startups

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By combining AI with physical dexterity, humanoids can perform complex tasks once limited to people, without the expensive facility modifications that traditional automation requires.

While manufacturing and warehousing use cases lead in early adoption, humanoids are expanding into healthcare, retail, and hospitality sectors, signaling widespread potential in industries that need human-like movement and flexibility.

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The humanoid robots market map

Now, our Book of Scouting Reports offers in-depth analysis on every single one of the private companies featured in the market map.

Combining CB Insights’ proprietary data and AI, scouting reports provide insight into each company’s:

• Funding history
• Headcount
• Key takeaways (including opportunities and threats)
• Commercial Maturity score
• Mosaic score

Download the book to see all 49 scouting reports.

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Now, we’re examining the critical metrics behind these winners, revealing potential acquisition targets, partnership opportunities, and emerging competitors before they reshape the market.

Below, we analyzed the 100 winners to understand how the cohort stacks up, the markets we’re seeing emerge, top investors in AI, and more.

Learn more about the AI 100 here

Some highlights from our analysis: 

• AI infrastructure shows a maturity gap despite massive funding. Despite the already enormous amount of capital raised in this category, AI infrastructure still has overall low Commercial Maturity Scores and sees a lot of early-stage activity with a specific focus on efficiency. These AI 100 winners are betting on next-generation solutions like specialized AI chips, novel computing architectures with reduced energy consumption and optimized inference, and infrastructure designed for multimodal workloads that current systems can’t efficiently handle. 
• Autonomous vehicles are accelerating beyond the hype cycle. The auto & mobility market ranks third by Mosaic score, with companies gaining significant commercial traction following Waymo‘s recent success in scaling its robotaxi operations. This momentum validates years of R&D investment and suggests we’re entering a new phase of AV deployment. Read more in our recent autonomous vehicle analysis.
• Multimodal AI is driving the biggest breakthroughs. Voice AI platform Cartesia leads the largest year-over-year Mosaic score jump (+321), alongside other companies pushing beyond text-only models toward integrated voice, vision, and reasoning capabilities. This shift represents the next evolution of AI, especially for embodied AI systems like humanoids, moving from single-modality tools toward systems that can understand and generate across multiple forms of media simultaneously. 

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Now, our Book of Scouting Reports offers in-depth analysis on every single one of the AI 100 winners, from infrastructure to horizontal to vertical applications.

Combining CB Insights’ proprietary data and AI, scouting reports provide insight into each company’s:

• Funding history
• Headcount
• Key takeaways (including opportunities and threats)
• Commercial Maturity score
• Mosaic score

Plus, the analysts behind this year’s AI 100 provide their perspective on every one of the winners.

Download the book to see all 100 scouting reports.

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While deal volumes remained mostly steady, funding increased 51% to $66.6B, with the majority of this going to infrastructure companies like OpenAI. 

Meanwhile, vertical AI is gaining momentum, with healthcare unicorns dominating Q1’s new unicorn cohort — a sign of investor confidence in AI’s increasing specialization.

Download the full report to access comprehensive data and charts on the evolving state of AI. 

Key takeaways from the report include:

• AI funding grows 51% QoQ to hit $66.6B — a new quarterly record — as industry incumbents secure mega-rounds. This boost was largely driven by a handful of major infrastructure players like OpenAI ($40B round), Anthropic ($3.5B Series E), and Safe Superintelligence ($2B Series B). Even without OpenAI’s massive round, Q1’25 would still represent the second-highest funding quarter ever (following Q4’24). Deal count decreased only slightly, falling 7% QoQ to 1,134. 
• Healthcare dominates the new AI unicorn pool. More than half of the 11 AI companies that reached $1B+ valuations in Q1 are developing healthcare solutions. These healthcare AI unicorns made up 30% of all new unicorns across VC and include Hippocratic AI (healthcare models and agents) and Insilico Medicine (AI drug discovery).
• AI agent companies lead M&A activity amid increasing consolidation. The 3 largest of 85 AI acquisitions in Q1’25 went to companies offering enterprise AI agent technology. The markets these companies occupy — like agent development platforms and multi-agent systems — boast among the highest average Mosaic scores across industries, reflecting strong company health and signaling the potential for more exits. 

We dive into the trends below.

AI funding reaches record $66.6B in Q1’25 as industry incumbents secure mega-rounds

AI funding grew 51% to $66.6B across 1,134 deals in Q1’25. This quarter’s funding total represents nearly two-thirds of all AI investment in 2024 ($101.5B), suggesting full-year 2025 funding will blow previous years’ tallies out of the water. 

The surge was fueled by mega-rounds concentrated among a few infrastructure giants, most notably OpenAI’s massive $40B VC round, along with Anthropic’s $3.5B Series E and Safe Superintelligence’s $2B Series B. Even without OpenAI’s landmark funding round, Q1 would be AI’s second-strongest funding quarter ever.

While total funding surged, the relatively stable deal count suggests larger deal sizes — especially to already established market leaders — rather than simply more companies receiving investment. In fact, in 2025 YTD, the median deal size of $5M represents a 4-year high. 

CBI customers: Track 17K+ AI companies

Healthcare dominates the new AI unicorn pool

While infrastructure companies received the lion’s share of funding, healthcare AI players led in new unicorn creation. 

Healthcare companies claimed the majority of new AI unicorns in Q1’25, with 6 out of 11 total AI companies reaching the $1B+ milestone. Even when looking at the venture landscape beyond AI, healthcare AI players drove nearly 1 in 3 new unicorn births in Q1. 

While healthcare AI unicorns are developing diverse applications across the care continuum, half of these newly minted unicorns apply AI to support provider workflows. These include:

• Hippocratic AI (patient follow-up)
• Abridge (clinical documentation)
• OpenEvidence (healthcare decision-making)

This trend highlights both growing demand for clinician-support tools and strong investor conviction in AI’s ability to deliver returns in the healthcare industry.

See every current AI unicorn

AI agent companies lead M&A activity amid increasing consolidation

Agentic solutions led the top AI exits in Q1’25, securing the 3 largest deals among 85 acquisitions — establishing agents as the primary focus of industry consolidation. 

These acquisitions align with the high Mosaic scores (which measure company health and growth potential on a 0-1,000 scale) across AI agent markets. Top agent categories all score well above the average of 370 across industries: autonomous agents & digital coworkers (721), AI agent development platforms (715), and multi-agent systems & orchestration (705).

The blockbuster exits of companies like Moveworks, Weights & Biases, and OfferFit show that enterprise buyers are increasingly seeking to build comprehensive agent solutions to gain a competitive edge. 

See rising markets in the CBI Market Leaderboard

MORE AI RESEARCH FROM CB INSIGHTS

• The AI agent market map
• AI 100: The most promising artificial intelligence startups of 2025
• Enterprise AI agents & copilots: Our growth projections for the $5B+ market 
• What’s next for AI agents? 4 trends to watch in 2025

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Despite this contraction, median deal size has climbed to $10M this year (up from $8.9M in full-year 2024), revealing that CVCs are making fewer but larger investments as economic uncertainty persists.

The quarter highlighted 2 other dominant forces reshaping the CVC landscape: US startups captured 70% of global CVC-backed funding — the 2nd straight quarter at 70%+ — while AI startups secured 7 of the top 10 CVC deals worldwide. This reflects an intensifying race among CVCs to secure competitive footholds in leading technologies before rivals gain the upper hand.

Download the full report to access comprehensive data and charts on the evolving state of CVC across sectors, geographies, and more.

Key takeaways from the report include:

• Deals continue their downward trend as investors remain selective. Global CVC deal volume fell 13% QoQ to 728 deals in Q1’25, reaching the lowest quarterly total since Q1’18. Mega-rounds ($100M+) accounted for 59% of the $18.7B in total funding, showing that CVCs are still making substantial bets in a more selective environment.
• US companies dominate CVC investment dollars. In Q1’25, US startups captured $13.1B (or 70%) of global funding from deals with CVC participation. Within the US, Silicon Valley maintained its leading position with $7.5B across 97 deals, underscoring its continued importance as a strategic hub for corporate investment.
• AI continues to command CVC attention and dollars. AI startups secured 7 of the 10 largest CVC-backed deals in Q1’25, with these deals representing 31% of all quarterly funding among CVC-backed deals. The biggest deal was Anthropic‘s massive $3.5B Series E round, backed by the venture arms of Cisco and Salesforce.
• Early-stage deal share holds steady at the highest level in over a decade. Early-stage investments made up 65% of all CVC deal activity in Q1’25, matching the high-water mark sustained annually since 2023. With the median early-stage deal size growing to $5.8M this year so far, CVCs are placing larger bets on nascent companies that have long-term growth potential.
• Salesforce Ventures leads with the strongest Q1 portfolio. Among CVCs with 5+ investments in Q1’25, Salesforce Ventures leads the way with the highest average Mosaic score, followed by Qualcomm Ventures. Salesforce Ventures’ Q1’25 investments include 2 of the largest rounds this quarter — Anthropic ($3.5B) and Together AI ($305M) — signaling the importance of AI in its growth strategy.

We dive into the trends below.

Deals continue their downward trend as investors remain selective

Global CVC deals fell 13% QoQ to 728, the lowest quarterly total since Q1’18. CVC-backed funding also declined 22% to $18.7B. 

Despite the pullback, $100M+ mega-rounds accounted for 59% of total funding, indicating that CVCs are still making large, strategic bets but in a more selective environment.

While the number of deals decreased, the median size of CVC-backed deals increased to $10M — up from $8.9M last year — as CVCs write larger checks for companies they believe will deliver long-term strategic value.

The shift toward fewer but larger deals reflects a broader flight to quality across venture capital. Notable mega-rounds in Q1’25 included Anthropic’s massive $3.5B Series E round, which represented nearly 19% of all Q1 CVC-backed funding globally and showcased the concentration of capital in market-leading companies.

US companies dominate CVC investment dollars

US companies captured 70% of global CVC-backed funding in Q1’25, securing $13.1B despite macroeconomic volatility. The US funding share represents the 2nd quarter in a row at 70% or above, up significantly from the historical norm of ~50% before 2023.

Silicon Valley maintained its position as the epicenter of CVC investment, attracting $7.5B across 97 deals — more than half the total US funding.

Several unicorn rounds powered the US’ strong funding quarter, including those from Anthropic, NinjaOne, Lambda, and Apptronik.

The capital concentration is striking given that US companies represented just 37% of global deal volume (269 of 728 deals). The substantial gap between deal share and funding share highlights a key regional difference in investment approach, with US deals ballooning in size. The median US deal reached $17M in Q1’25 — over 50% more than Europe, the next highest region, at $10.9M.

However, as corporate uncertainty grows due to shifting tariff policies, the US’ funding dominance will be a critical trend to monitor in the coming quarters.

Hear from CBI analysts on the global impact of tariffs

AI continues to command CVC attention and dollars

AI dominated the biggest CVC investments in Q1’25 — securing 7 of the top 10 deals — as CVCs place massive bets on startups with the potential to reshape industries.

CVCs are investing in AI companies across diverse areas. These range from general-purpose AI agents & copilots to hardware applications like Apptronik’s AI-powered industrial humanoid robots.

Other leading CVC-backed AI deals in Q1’25 include:

• Isomorphic Laboratories: $600M (backed by Google Ventures, NVentures) in a record-breaking round for AI-powered drug discovery
• Lambda: $480M (In-Q-Tel, NVentures) for AI computing infrastructure and cloud services
• Together AI: $305M (Prosperity7 Ventures, Salesforce Ventures, SE Ventures, SK Telecom Ventures) for building open-source foundation models and infrastructure
• Harvey: $300M (Google Ventures, OpenAI Startup Fund, REV Venture Partners) for specialized AI solutions for the legal industry
• Innovaccer: $275M (Danaher Ventures, Microsoft’s M12) for healthcare data integration and AI-powered analytics

For parent corporations, these investments go well beyond financial returns. They provide strategic access to technologies that could determine competitive advantage in the AI era.

Track the latest CVC-backed AI deals

Early-stage deals hold at the highest levels in over a decade

Early-stage investments remain at a record share of CVC activity, accounting for 65% of all deals in Q1’25 — matching the same level seen over the past 2 years and up 7 percentage points from where it was in 2021.

The strategic shift comes with increasing commitment levels, as the median early-stage deal size grew to $5.8M in Q1’25. Rather than spreading smaller amounts across many startups, CVCs are making substantial, focused bets on promising early-stage companies.

Regional strategies show notable differences: Asia leads with 39% of early-stage CVC deals, compared to 33% in the US and 21% in Europe. This suggests that corporate investors in Asia are particularly aggressive in securing access to emerging technologies at the earliest possible stage.

Across all markets, this pronounced shift toward early-stage investing reflects a fundamental change in CVC strategy: corporate investors are prioritizing gaining early access to innovation rather than supplying later-stage growth capital, positioning themselves to shape technological development from the beginning rather than joining after validation.

Salesforce Ventures leads with the strongest Q1 portfolio

Among CVCs with 5+ investments in Q1’25, Salesforce Ventures leads with the highest average Mosaic score for its Q1’25 bets (891 out of 1,000), followed by Qualcomm Ventures (840). Salesforce Ventures’ Q1’25 investments include 2 of the largest rounds this quarter: Anthropic ($3.5B) and Together AI ($305M).

Meanwhile, Google Ventures was the most active CVC in Q1’25 with 17 companies backed, followed by Japan-based investors Mitsubishi UFJ Capital and SMBC Venture Capital with 15 companies each. With 11 companies each, In-Q-Tel and Mizuho Capital rounded out the top five, highlighting the dominance of US- and Japan-based corporate investors.

Track top CVC-backed companies by Mosaic score

MORE VENTURE RESEARCH FROM CB INSIGHTS

• State of Venture Q1’25 Report
• State of Fintech Q1’25 Report
• State of Digital Health Q1’25 Report

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Given this momentum, the ecosystem is larger and more challenging to navigate than ever.

Our annual AI 100 list is designed to cut through this noise and highlight the next wave of AI winners, with a focus on early-stage players that are showing strength in terms of market traction, investor quality, and talent.

Leveraging CB Insights datasets such as deal activity, industry partnerships, team strength, investor strength, patent activity, and our proprietary Mosaic Scores, we selected 100 winners out of a cohort of 17K+ companies. We also analyzed CB Insights’ exclusive interviews with software buyers and dug into Analyst Briefings submitted directly to us by startups.

Below, we map out the winners, categorizing them based on their core offering. Key trends and category definitions follow. Customers can track activity of all of these companies in this watchlist. 

Please click to enlarge. Data as of 4/23/25.

CBI customers: Get data on the winners

Key takeaways on the AI 100

1. AI agents dominate the conversation. These applications, which automate tasks and processes for human users, are the next wave of genAI. Having made their way into virtually every horizontal and enterprise function, AI agents are also coming for infrastructure and verticalized applications. AI agents and supporting infrastructure make up 21% of this year’s companies, and the investors we spoke with consistently cited this space as a priority. 
2. ML security has become table stakes. The need to secure AI applications has grown in lockstep with the proliferation of genAI and agentic AI. 46% of strategy team leaders point to security as the primary barrier to genAI adoption, according to a recent CB Insights survey. Machine learning security companies are hardening AI algorithms and foundational models like LLMs, while also defending against increasingly sophisticated AI-powered attacks. 
3. AI observability and governance are critical gaps. Widespread use of AI is exposing the technology’s cracks — hallucinations, lack of orchestration, and output inaccuracies. It’s clear that AI ubiquity can’t exist without robust monitoring. Companies are rising to meet this need. Startups in this year’s list cover areas like observability and governance, while a small cohort also monitors AI agents to ensure reliability and compliance.   
4. The future is physical. Looking ahead, AI will evolve beyond software AI agents to a physical state. Advances in disparate areas of AI development — including robotics, multimodal image and voice models, edge computing, synthetic data, and spatial intelligence — provide the scaffolding for physical AI, which pairs AI software with hardware to take action in physical environments. Industrial humanoids represent an early manifestation of this, while future permutations could include fully autonomous defense drones, home companion robots, and more.
5. Vertical applications are exploding. In 2024, the horizontal companies in this AI 100 cohort received more funding than their vertical and infrastructural counterparts — $1.6B compared to $1.2B each for infrastructure and vertical. But in 2025 so far, the funding picture looks very different: Vertical winners lead the way with $1.1B in funding raised.

Category breakdown

AI INFRASTRUCTURE 

On the foundation model front, infrastructure newcomers are rapidly releasing models that rival industry leaders, signaling a maturing market where technical excellence and novel approaches increasingly compete with raw computing power. We identified winners across large language, edge, reasoning, small language, and multimodal models. 

Meanwhile, as AI applications — particularly agents — become more autonomous and widespread, the need for robust monitoring, governance, and cybersecurity solutions has grown in lockstep. 

We’ve heard this in our conversations with AI investors, as well. Mozilla Ventures, a lead investor in Credo AI, views governance as a strategic imperative. Mohamed Nanabhay, Managing Partner, notes: 

 “…We think that the AI governance sector itself will take on a crucial role of creating value for enterprises, allowing companies that leverage governance to deploy AI faster through the reduction of risk with a greater competitive advantage as a result.”

Category definitions:

DATA

• Synthetic data: Artificially generated or altered information that mimics real-world data without privacy concerns. Aaru uses a multi-agent approach to create population simulations for predictive decision-making applications like consumer behavior and electoral modeling.  
• Data preparation & curation: Tools and platforms that clean, transform, label, and organize data to make it suitable for AI training and deployment, encompassing data cleaning and specialized data processing. Unstructured, for instance, helps organizations capture unstructured data from various documents and convert it into AI-friendly formats such as JSON to train LLMs.
• Vector databases: Solutions that provide enterprises with an easy way to store, search, and index unstructured data at a speed, scale, and efficiency that current relational (and non-relational) databases cannot offer. For example, Qdrant provides an open-source vector database that allows developers to build production-ready applications that use nearest neighbor search functionality.

DEVELOPMENT & TRAINING

• Foundation models: Pre-built AI algorithms and architectures that can be deployed, fine-tuned, or integrated into applications, spanning general-purpose foundation models and specialized domain-specific models. This category includes large language, edge, reasoning, small language, and multimodal AI models. For instance, Archetype AI‘s Newton model processes multimodal sensor data and natural language to provide insights and predictions about physical environments.
• Agent building & orchestration: This category covers AI agent development platforms for building, orchestrating, and monitoring agents. Companies like LangChain provide a framework for building context-aware reasoning applications with tools for debugging, testing, and monitoring app performance across the entire application lifecycle.
• Computer vision & spatial intelligence: Technology that enables AI systems to understand, interpret, and interact with physical spaces and 3D environments, including mapping, navigation, and spatial data processing capabilities. Notably, World Labs develops Large World Models (LWMs) that enable AI systems to perceive, generate, and interact with both virtual and real 3D environments using spatial intelligence.

OBSERVABILITY & EVALUATION

• AI observability platforms: These platforms monitor, measure, and assess AI model performance, reliability, and outputs, including tools for testing, benchmarking, and continuous improvement of AI systems. For instance, Arize’s platform allows teams to monitor, diagnose, and improve the performance of AI models and applications in production through tools based on open-source standards that integrate with existing AI infrastructure.
• Governance: Solutions that establish policies, processes, and controls for responsible AI development and deployment, covering risk management, compliance, ethical oversight, and transparency requirements. For example, Credo AI offers a platform that automates AI oversight, risk management, and regulatory compliance while providing AI auditing to ensure system integrity and fairness.
• Machine learning security (MLSec): Technologies that protect AI systems from vulnerabilities, attacks, and data breaches, including techniques for securing model training, inference, and data pipelines. Solutions developed by companies like Zama enable computation on encrypted data, allowing for privacy-preserving machine learning across industries that require data privacy and security.

ACCELERATED COMPUTING & HARDWARE

• Edge: Platforms that provide the infrastructure and models to operate AI on “edge” devices such as tablets, IoT, autonomous vehicles, or smartphones. For example, EdgeRunner AI constructs an ensemble of small, task-specific models that work together to solve complex problems locally on devices, ensuring data privacy and security for heavily regulated industries.
• Photonics: Solutions that use light (photons) instead of electrons for data processing, with the potential to significantly increase computing speeds. Companies in this category provide memory, interconnects, and system architecture. Xscape Photonics develops bandwidth-efficient photonics solutions to support AI/ML infrastructure. 
• Quantum: Companies providing novel techniques like model compression and hardware to support quantum commercialization. Multiverse Computing provides AI model compression technology to enable quantum AI workloads and processing.
• Chips: Traditional chips, in addition to chips to support new AI technologies. Etched develops chips designed specifically for transformer inference, capable of processing extensive data for applications such as real-time voice agents and content generation.

HORIZONTAL AI

This category includes industry-agnostic solutions across visual media, text, code, audio, and interfaces. These function-specific solutions address common business needs regardless of industry, offering specialized intelligence that complements both vertical applications and foundational infrastructure.

AI agents in particular are beginning to upend the way in which enterprises think about software. Decibel Partners, a lead investor in multi-agent platform Dropzone AI, sees a movement toward productizing agents as full systems. Jéssica Leão, a Partner at Decibel, articulates this vision further:

“…We’re going to see the software world change because, again, you’re selling agents almost as if you’re selling back-end software.”

Horizontal AI solutions are increasingly tailored to serve distinct business functions while remaining broadly deployable. Startups in this category are developing sophisticated AI systems that excel in capabilities like content generation, customer support, process automation, and software development — all of which can be applied across industries. 

Category definitions:

• Content generation: AI systems that create text, images, video, and other media forms — spanning automated content production and multimodal generation. For example, Moonvalley’s genAI video model helps filmmakers by enabling prompt adherence, motion generation, and physics simulation using cleaned, fully licensed data.
• Customer service: AI agents that autonomously handle customer service tasks or augment human agents. Sierra‘s platform, for instance, provides intelligent agents for customer support that engage in personalized interactions and integrate with existing call center technologies.
• Cybersecurity: AI-powered solutions that detect, prevent, and respond to digital threats, vulnerabilities, and attacks, covering network security, threat intelligence, and automated incident response. Companies like Binarly use AI to detect and remediate vulnerabilities in firmware and software supply chains.
• General-purpose humanoids: AI systems embedded in robotic bodies that mimic human capabilities, enabling physical interaction through perception and manipulation. For example, Figure develops autonomous humanoid robots that combine human-like dexterity with AI to perform a variety of tasks across industries like manufacturing, logistics, warehousing, and retail.
• Process automation: Intelligent systems that autonomously handle repetitive business workflows, increasing efficiency by eliminating manual tasks. Orby AI offers a platform that observes enterprise processes and generates executable automations — particularly for complex, data-heavy operations in industries like tech and finance. 
• Software development & coding: AI solutions that assist with software development, code generation, debugging, and programming tasks, including automated code completion tools. For instance, Poolside offers foundation models and APIs that can be fine-tuned using a company’s own codebase and documentation to support internal dev teams.
• Video security: Technologies that enable real-time analysis of video feeds, supporting faster detection and response to security threats. Coram AI develops cloud-based security camera systems with features like real-time AI alerts and natural language video search, allowing businesses to monitor properties remotely without extensive hardware replacements.

VERTICAL AI 

Vertical AI is on the rise, with this year’s vertical winners surpassing the other category winners to capture over $1B in combined funding in 2025 YTD. They span 10 industries that represent a convergence of high-value problems, rich data availability, and regulatory momentum.

Some of the VCs we spoke with see specialization as the way of the future. Lila Tretikov, Partner and Head of AI Strategy at New Enterprise Associates (a lead investor for Twelve Labs, World Labs, and Orby AI), told us:

“We believe that there is going to be specialization, even within the model layer. And there’s going to be innovation in this layer, especially as we look at verticalization for specific use cases.”

The most well-represented verticals on this year’s list are healthcare (8 companies) and life sciences (6 companies). The healthcare industry as a whole is seeing breakthrough applications across multiple AI modalities — from agentic AI systems that can augment clinical workflows, to advanced machine vision for medical imaging analysis, to AI-accelerated drug discovery platforms that dramatically reduce R&D timelines.

This year’s cohort also saw significant representation in gaming & virtual assets (5 companies), finance & insurance (4 winners), and aerospace & defense (4 winners). 

Category definitions:

• Aerospace & defense: AI solutions designed for aerospace engineering, aviation operations, military applications, and defense systems, including autonomous navigation and threat detection technologies. For instance, Quantum Systems creates eVTOL unmanned aerial systems that serve critical defense applications, most notably in Ukraine. 
• Auto & mobility: AI applications for autonomous vehicles, transportation optimization, fleet management, and mobility services. Companies like Wayve are developing AI systems that use LLMs to provide real-time natural language explanations of driving decisions, helping improve users’ confidence.
• Energy: Platforms that optimize energy production, distribution, and sustainability, including battery intelligence and AI assistance for electric grids. For example, Liminal leverages ultrasound and machine learning inspection solutions to improve battery cell quality, cost-effectiveness, and safety while enabling confident scaling of production. 
• Finance & insurance: AI solutions for financial services, banking, investment, and insurance sectors, covering payments, risk assessment, and portfolio monitoring. Skyfire’s financial stack enables AI agents to perform transactions without credit cards or bank accounts, allowing businesses to monetize their products, services, and data through AI agents.
• Gaming & virtual assets: AI technologies that enhance gaming experiences, virtual environments, digital asset management, and immersive entertainment, including content generation and NPC (non-player character) intelligence. Altera‘s platform creates digital human beings that can interact with users and perform tasks autonomously, bringing empathy and human-like traits to digital interactions.
• Healthcare: AI applications focused on clinical care delivery, medical operations, and patient management, including tools for clinical documentation automation, medical imaging analysis, decision support systems, remote patient monitoring, and healthcare supply chain optimization. In the dental field, Overjet provides an AI platform that enhances clinical care through radiographic analysis and optimizes claims processing for providers and payers.
• Life sciences: AI solutions for pharmaceutical research, drug discovery, protein engineering, biological data analysis, and therapeutic development, including platforms for multiomics analysis, antibody design, foundation models for biology, and scientific experiment automation. Lila Sciences has developed a platform that integrates AI with autonomous laboratories to design, conduct, observe, and redesign experiments for scientific discovery.
• Legal: AI tools for legal research, document analysis, contract management, compliance, and legal workflow automation, including case management, due diligence, and contract review. AI-powered tools like Eve help law firms streamline the full case lifecycle from intake to litigation by automating case intake, drafting legal documents, and managing discovery processes.
• Manufacturing: Technology that optimizes industrial processes like factory automation, using virtual development and simulation. PhysicsX applies machine learning to physics simulations that optimize design and engineering processes across industries including aerospace, medical devices, and electric vehicles.
• Supply chain: AI solutions that enhance logistics and supply chain operations, including warehouse management and route optimization & visibility. Dexory combines stock-scanning robots with a digital twin platform to provide real-time inventory and warehouse analytics for logistics and supply chain operations.

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

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It looks like voice AI may have found its sweet spot: ordering fries with that.

Yum! Brands — which owns Taco Bell, KFC, and Pizza Hut and has a larger restaurant footprint than any other company globally — recently announced a partnership with Nvidia to deploy AI (including AI voice ordering) throughout hundreds of restaurants starting in April. 

Similarly, Jersey Mike’s Subs has partnered with SoundHound on a 50-store pilot of AI voice ordering, while Wendy’s now uses Google Cloud LLMs to process orders in English and Spanish.

Voice AI stands to reduce labor costs in high-turnover positions while also increasing order throughput and accuracy. It also means staff can be redeployed to food preparation or customer service roles that drive higher satisfaction.

But fast food is just the tip of the iceberg for voice AI.

Below, we get into:

• Why voice AI matters 
• Market maturity
• Challenges to adoption

Why does voice AI matter?

For customer interactions, voice conversations offer a far more expressive mode of communication than text-based channels. 

Yet the industry remains stuck in a purgatory of robo-call decision trees and endless holds. 62% of customer calls to SMBs go unanswered, while upwards of 70% of business calls that connect still end up putting customers on hold, with most hanging up within minutes. 

Advances in AI speech models could break this cycle. Voice AI models are shifting toward processing audio directly — rather than needing to translate it to text, process it using an LLM, then convert it back into speech — and are getting closer to the cadence of human conversation (<300ms latency).

The progress has fueled a surge in equity funding to voice AI solutions, which grabbed $2.1B in 2024, per CB Insights’ funding data. Momentum has continued in 2025 so far, with companies raising nearly $500M in Q1’25.

ElevenLabs‘ $180M round from investors including a16z, Salesforce Ventures, and Sequoia Capital was a big part of this year’s strong start. ElevenLabs has already hit $100M in ARR — just 3 years after its founding.

On the whole, though, the voice AI market remains in its early stages — and faces growing pains.

The market is still nascent

Most of the voice AI market remains in the earlier stages of commercial maturity, with 85% in levels 1, 2, or 3 on CB Insights’ Commercial Maturity scale. More than half are still developing or validating their products, while 39% are beginning commercial distribution and starting to gain customers.

Most startups here were founded in just the last 3 years, as the chart below demonstrates. 2023 was a breakout year, seeing the number of companies founded grow 2x year-over-year, from 35 to 70.

This growth has been driven by advancements in voice AI models — including OpenAI‘s Realtime API for speech-to-speech applications, launched in late 2024 — which jumpstarted applications across use cases.

One additional signal that voice is hot: companies building voice AI applications are making up larger chunks of Y Combinator’s recent cohorts.

CBI customers can dive into the data on 270 companies developing voice AI capabilities — with a focus on voice generation — here.

Growing pains

Despite the excitement, challenges remain around reliability and trust. 

Voice AI agents still struggle with complex conversations and unpredictable inputs, leading most enterprises to start out by deploying them in low-stakes scenarios.

In theory, fast-food ordering should be a natural fit — interactions are brief and highly predictable. The AI only needs to understand a limited vocabulary of items and modifiers.

But the reputational risk of even the occasional mishap can be high. McDonald’s, for instance, started a voice AI pilot with IBM back in 2021, but pulled it in 2024 after videos of inaccurate orders went viral on TikTok. 

Customer acceptance of voice AI interaction also varies dramatically by region. As one Cognigy customer told us:

Meanwhile, a strategic divide is emerging in the voice AI market: cloud vs. edge processing.

Cloud-based solutions from tech giants offer advanced capabilities but raise privacy concerns, while edge-based platforms process data locally with better privacy but more limited features.

A medtech executive highlighted this tradeoff, telling us they chose Sensory over Microsoft or Amazon despite losing out on more robust capabilities:

This divide will shape which players win in different sectors, with edge solutions likely dominating in sensitive industries like healthcare and financial services, while cloud platforms prevail in consumer and retail applications.

For more on how AI will shape every aspect of the customer experience, get the free report here.

RELATED RESOURCES:

• Data on 270 voice AI companies
• Market report on voice AI development platforms
• State of Venture Q1’25 Report

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

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Opportunities across stages and geographies have fueled growth in deal sizes globally. So far in 2025, the median deal size sits at a record $3.5M.

While AI continues to dominate headlines and venture activity, sectors like fintech, digital health, and retail tech all recorded quarterly funding increases as investors diversify beyond core AI infrastructure plays.

Download the full report to access comprehensive data and charts on the evolving state of venture across sectors, geographies, and more.

Below, we break down the top stories from this quarter’s report, including:

• Quarterly funding jumps to $121B, even as deal count keeps falling
• AI now drives 1 in 5 global venture deals
• Eight early-stage AI companies raise $100M+ mega-rounds
• Early-stage deal sizes pace at an all-time high
• Billion-dollar M&A exits hit a new quarterly record

We also outline the key trends shaping venture dealmaking for the rest of 2025 — from AI agent specialization and the voice AI boom to crypto’s rebound.

Let’s dive in.

Top stories in Q1’25

1. Quarterly funding jumps to $121B, even as deal count keeps falling

Q1’25 saw global venture funding rise to $121B — the highest quarterly total since Q2’22 — driven by OpenAI’s $40B raise, which values the company at $300B. This ties OpenAI with ByteDance as the second-highest-valued private company globally (behind SpaceX at $350B).

The OpenAI funding round — led by SoftBank and backed by Microsoft, Thrive Capital, and others — marks the largest private funding round in history. Even excluding this deal, total funding in Q1’25 would have reached $81B, still the second-highest quarterly figure since Q3’22.

However, global deal count slid for a fourth straight quarter, to 5,846 deals, down 7% QoQ and 28% YoY.

The stark contrast between soaring funding and declining deal count highlights growing capital concentration. 

Mega-rounds (deals worth $100M+) accounted for 70% of all funding this quarter, up from 60% in Q4’24. A total of 145 mega-rounds closed in Q1’25 — the highest quarterly total since Q3’22, which saw 157.

While AI startups remain the primary beneficiaries of this capital concentration — grabbing more than half of the quarter’s funding — other sectors are showing resilience. Fintech funding increased 18% quarter-over-quarter to $10.3B, retail tech rose 18% to $6.5B, and digital health grew 47% to $5.3B.

2. AI now drives 1 in 5 venture deals

The influence of AI on venture capital continues to grow, with AI companies now capturing 20% of all venture deals globally — a new high, and up 2x since OpenAI’s launch of ChatGPT in 2022. 

In absolute numbers, AI companies secured 1,134 deals in Q1’25 — a 7% decline from the previous quarter but still the fourth straight quarter with over 1,100 AI deals.

The composition of AI dealmaking is evolving. Early-stage deals (seed and Series A) made up 70% of all AI deals in Q1’25, down from 75% in full-year 2024. Correspondingly, late-stage deal share has increased from 6% to 9%, indicating market maturation as more AI companies progress to advanced funding stages.

The focus of AI dealmaking has also evolved. While infrastructure investments dominated the early AI boom, we’re now seeing greater emphasis on vertical solutions and application-layer platforms that address specific industry challenges. Notable exceptions exist in emerging categories like voice AI, where infrastructure still attracts significant investment.

Geographically, US-based AI companies secured 52% of global AI deals in Q1’25, while Asia and Europe grabbed 21% a piece.

Explore 15,000+ AI companies in the Expert Collection

3. Eight early-stage AI companies raise $100M+ mega-rounds

Q1’25 set a new record with 8 early-stage AI companies raising rounds of $100M or more. These 8 companies raised a combined $1.8B — with an average round size of $222M — highlighting investors’ willingness to place substantial bets on AI startups earlier than ever.

The companies represent a diverse range of AI applications:

• Isomorphic Laboratories: $600M for AI drug discovery, spun out of DeepMind
• Apptronik: $403M for humanoid robots
• Lila Sciences: $200M for scientific research automation
• The Bot Company: $150M for household robots
• Endless: $110M for AI-led Web3 developer tools
• Nexthop: $110M for cloud-native AI infrastructure
• Reflection AI: $105M for coding AI agents
• MainFunc: $100M for an agentic search engine

What unites these companies is their focus on specific industry or technical challenges — not general-purpose AI models. This same trend appears among late-stage players that raised deals in Q1’25, with companies emphasizing enterprise applications, vertical use cases, and infrastructure optimization. 

The shift from infrastructure to applications also plays out at the tech market level. Among the 1,400+ tech markets that CB Insights tracks, those in the below chart saw the greatest number of AI deals in Q1’25. 

While LLM developers remain the top target for deals, they saw no growth in Q1’25 vs. Q1’24. On the other hand, vertical applications in industrials and healthcare — where AI is measurably improving automation — led in terms of YoY growth.

The top three vertical markets for AI deal growth in Q1’25 were automated guided vehicles (AGVs) and autonomous mobile robots (AMRs), radiology diagnostics — particularly those focused on multiple imaging modalities — and clinical documentation solutions.

See how markets stack up in the CBI Market Index

4. Early-stage deal sizes pace at an all-time high

The median early-stage deal size reached $2.7M in Q1’25, up from $2M in full-year 2024 — a 35% increase. This jump reflects both investors’ willingness to place larger bets on promising teams and the increased capital requirements for competitive AI development.

The increase is particularly notable against a backdrop of declining deal volume — investors are concentrating resources on fewer, more promising opportunities rather than spreading capital across a wide range of startups.

This environment creates both opportunities and challenges for founders. Well-positioned early-stage companies can secure larger initial rounds, but expectations for progress and growth are similarly elevated. The bar for follow-on funding will be higher for mid-stage rounds.

5. Billion-dollar M&A exits hit a new quarterly record

Q1’25 set a new record for billion-dollar M&A activity, with 12 VC-backed exits exceeding $1B in value, surpassing the previous high of 11 seen in both Q1’00 (dot-com bubble) and Q4’20 (peak ZIRP era). These 12 transactions had a combined value of $56B, driven primarily by Google‘s landmark acquisition of cloud security company Wiz.

The Wiz deal now stands as the most valuable M&A deal ever for a VC-backed private company, exceeding Meta‘s WhatsApp acquisition by more than $10B. It also marks Google’s largest acquisition to date — more than double the size of its Motorola Mobility purchase in 2012 — and sets a new record for cybersecurity exits, eclipsing Cisco’s $28B acquisition of Splunk.

The Wiz deal highlights the growing focus among big tech companies on AI-driven cloud security as enterprises prioritize securing their expanding digital footprints. 

It’s also part of a broader trend of high-profile unicorn exits that includes both IPOs (CoreWeave) and M&A transactions (Moveworks, Weights & Biases). 

In fact, looking back to 2024, billion-dollar IPOs delivered strong returns — averaging a 97% increase in market cap post-listing. This bodes well for other IPO hopefuls looking to brave the public markets in the coming months.

Predictions for venture dealmaking in 2025

Below, we use signals from public-company earnings calls, startup financing trends, and business relationships to predict which trends will dominate venture activity through the rest of 2025.

AI agents “niche down” and gain enterprise buy-in

AI agents are transitioning from concept to commercial application. They’ve become a frequent topic on corporate earnings calls, and according to a December 2024 CB Insights survey, 63% of organizations said they are placing significant importance on AI agents over the next 12 months. All respondents reported at least experimenting with agents.

These LLM-based systems represent an evolution beyond copilots. They can autonomously handle complex tasks — from sales prospecting to compliance decision-making — with limited human input. The market is expanding rapidly, with CB Insights data showing that over half of companies in the space were founded since 2023.

Investor interest is surging in parallel. AI agent startups saw more than 200 equity deals in 2024 — and activity is pacing toward similar levels this year.

Key investment themes emerging in the space include:

• Specialized agents for specific business functions (sales, legal, finance)
• Agent orchestration platforms that manage multiple agentic systems
• Safety and alignment tools for ensuring agent behaviors match human intentions
• Enterprise-grade agents with robust permissions and security frameworks

As agents become more capable and trustworthy, adoption will accelerate across industries.

Read more from our AI agent coverage:

• What’s next for AI agents? 4 trends to watch in 2025
• The AI agent market map

CBI customers: Track 250+ AI agent companies

Voice AI takes off amid technical advances

Voice AI is undergoing a technical transformation as models shift toward processing audio directly — bypassing the text intermediation stage — and approaching human-like conversation latency of under 300ms.

This technical progress has fueled substantial investment, with voice AI solutions raising $2.1B in 2024 and nearly $500M in Q1’25. 

One standout is ElevenLabs, which reached $100M in ARR just 3 years after its founding and raised a $180M round in January from investors including a16z, Salesforce Ventures, and Sequoia Capital.

Despite these promising signals, the voice AI market remains in early development. CB Insights data shows approximately 85% of companies in the space are at levels 1-3 on the Commercial Maturity scale. Nearly half are developing or validating their products, while 39% have just begun commercial distribution.

As voice interfaces become more natural and capable, we expect to see investment opportunities emerge in several areas:

• Domain-specific voice applications for industries like healthcare and legal
• Voice AI trained on local languages not typically covered by general-purpose AI systems
• Voice-first UI/UX for both consumer and enterprise applications

Crypto & blockchain rebound

After weathering a prolonged crypto winter, blockchain technologies are experiencing renewed institutional interest. Funding to crypto/blockchain companies reached $6.6B in Q1’25, putting the space on track to surpass $20B in annual funding. Earnings call mentions have climbed accordingly. 

Several crypto companies now rank among the most likely IPO candidates, with platforms like Blockchain.com and Kraken showing IPO probabilities 64x higher than the average company tracked by CB Insights — a notable shift in public-market viability for the sector. 

Another trend to watch is the growing institutional and government focus on stablecoins, as regulators develop frameworks to incorporate these digital assets into the traditional financial system. 

Defense tech comes into focus

Military technology is entering a new era as investment shifts toward autonomous systems and AI-driven capabilities.

According to former Joint Chiefs of Staff Chairman General Mark Milley, smart machines and robotics could account for one-third of the US military presence within the next 15 years.

Funding to AI defense tech startups has already reached $1.5B this year — leading to a projected $6B by year-end. Last quarter saw earnings call discussion of defense reach an all-time high.

Much of this activity centers on multidomain operations (MDO) technologies — integrating systems across land, sea, air, space, and cyber — where AI is accelerating mission planning, threat detection, and battlefield connectivity. Major defense contractors are forming partnerships with AI startups to enhance battlefield management systems, mission planning capabilities, and integrated defense connectivity platforms.

As geopolitical tensions persist, defense tech investment is likely to continue growing, with particular focus on autonomous systems, AI-enhanced battlefield analytics, and advanced cybersecurity solutions for critical infrastructure.

See 240+ AI defense companies in this market map

Conclusion

The venture capital landscape in Q1’25 reflects key contrasts: record funding alongside declining deal count, significant early-stage deals vs. heightened expectations for follow-on capital, and a resurgence in billion-dollar exits despite broader market caution.

AI continues to influence capital allocation decisions across the venture ecosystem, but we’re seeing a shift from general infrastructure investments to specialized vertical applications and industry-specific solutions. Meanwhile, sectors beyond AI are showing resilience, with fintech, digital health, and retail tech all posting quarterly funding increases.

For investors, the data suggests maintaining a disciplined approach to AI investments while remaining alert to opportunities in adjacent sectors. The companies that successfully blend AI capabilities with sustainable business models will emerge as the defining ventures of this era.

For more insights on venture trends and emerging technologies, explore our related resources:

• The AI agent market map
• 7 tech M&A predictions for 2025
• State of AI Report: 6 trends shaping the landscape in 2025
• 15 tech trends to watch closely in 2025

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

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AI chatbots saw a record 427M app downloads last quarter — up 42% vs. Q3.

Now Meta wants in on the action. 

The tech giant reportedly plans to spin Meta AI into a standalone app to compete with ChatGPT, Google’s Gemini, Perplexity, and other chatbot apps.

ChatGPT is still king with nearly a quarter of AI chatbot app downloads in 2024 and 400M weekly active users across platforms (not just mobile).

But Meta has a massive in-built user base, including ~700M people who already interact with Meta AI features each month across apps like Facebook and Instagram.

The battle for attention is on.

Source: X

One of the differentiators for social AI applications will be emotional intelligence — an area where OpenAI’s latest model, GPT-4.5, shows promise. 

While many headlines have focused on the model’s eye-watering costs, one notable advance is its reported ability to interact with greater empathy (an area where Anthropic’s Claude has so far been superior).

This matters because the more natural AI sounds, the easier it will be for consumers to see it fitting into their lives.

It also makes AI even more formidable in both personal and business settings if the AI can be both higher IQ and EQ than most of us pesky ol’ humans.

Businesses are catching on: More public cos are citing AI as a “friend” or “companion” on earnings calls in an effort to make B2C services more personal.

Mercedes-Benz, for instance, envisions drivers chatting with its MBUX voice assistant (which is built on ChatGPT) like a friend.

Source: CB Insights — Mercedes-Benz Q4’24 earnings call

Beyond emotional connection, AI developers are also making their chatbots more useful through agentic capabilities. This dual focus on both feeling and function will shape the competitive landscape moving forward.

While still constrained by reliability and access issues, web-browsing agents like OpenAI’s Operator signal a future where humans interact regularly with AI agents that take actions on their behalf.

Already nearly every tech giant, plus leading LLM developers like OpenAI and Anthropic, have developed AI agents or are building out tools for others to develop them.

In a head-to-head matchup, OpenAI and Meta would bring distinct sets of advantages.

OpenAI has already built user habits with ChatGPT and is now layering agent capabilities on top. Meta must convince users its AI offering brings something meaningfully different.

But Meta’s experience in the social realm, combined with its existing algorithms, could give it an edge in creating AI that feels like it belongs in human conversations.

Watch for both companies to rapidly iterate on their consumer agent offerings in the coming months.

Related AI research from CB Insights:

• What’s next for AI agents? 4 trends to watch in 2025
• The future of the customer journey: AI agents take control of the buying process
• The foundation model divide: Mapping the future of open vs. closed AI development
• State of AI Report: 6 trends shaping the landscape in 2025

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But AI and blockchain solutions are driving innovation to create new revenue streams and stoke the existing ones. Early-stage deals in those spaces helped drive a rally in funding and dealmaking in gaming in 2024. Annual funding nearly tripled to $3.2B across 317 deals, with early-stage companies securing 77% of investments — up from 70% in 2023. 

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However, global CVC deal count dropped to its lowest level since 2018 as CVCs become more selective.

Download the full report to access comprehensive data and charts on the evolving state of CVC across sectors, geographies, and more.

Key takeaways from the report include:

• CVC-backed funding grows, deal activity slows. Global CVC-backed funding increased 20% YoY to $65.9B, but deal count fell to 3,434, the lowest level since 2018. All major regions saw deal volume declines, with Europe dropping the most at 10% YoY.
• CVCs are all in on AI. AI startups captured 37% of CVC-backed funding and 21% of deals in 2024 — both record highs. Counter to the broader decline in deals, CVCs ratcheted up AI dealmaking by 13% YoY as they race to secure footholds in the space before competitors gain an insurmountable edge.
• The flight to quality continues. Among deals with CVC participation, the annual average deal size hit $27.3M in 2024, tied for the second highest ever. Amid fewer deals, CVCs are increasingly aggressive when they do decide to invest.
• Early-stage deals dominate. Early-stage rounds comprised 65% of 2024 CVC-backed deals, tied for the highest share in over a decade. Biotech startups made up half of the top 20 early-stage deals.
• CVC-backed funding plummets in Asia. In 2024, Asia’s CVC-backed funding dropped 34% YoY to $7B — the lowest level since 2016. China is leading the decline, with no quarter in 2024 exceeding $0.5B in funding. CVCs remain wary of investing in the country’s private sector.

We dive into the trends below.

CVC-backed funding grows, deal activity slows

Global CVC-backed funding reached $65.9B, a 20% YoY increase. The US was the main driver, increasing 39% YoY to $42.8B. Europe also saw CVC-backed funding grow 18% to $12.3B, while Asia declined 34% to $7B.

$100M+ mega-rounds also contributed to the rise, ticking up 21% YoY to 141 deals worth over $32B in funding.

Meanwhile, deal count continued its decline, as both annual (3,434 in 2024) and quarterly (806 in Q4’24) totals reached their lowest levels in 6 years.

Annual deal volume fell by at least 6% YoY across each major region — the US, Asia, and Europe — with Europe experiencing the largest decline at 10%.

However, Japan-based CVC deal volume remains near peak levels, suggesting a more resilient CVC culture compared to other nations. Two of the three most active CVCs in Q4’24 are based in Japan: Mitsubishi UFJ Capital (21 company investments) and SMBC Venture Capital (15).

Track recent activity from 1,000+ CVCs

CVCs are all in on AI

AI is driving CVC investment activity, much like the broader venture landscape. In 2024, AI startups captured 37% of CVC-backed funding and 21% of deals, both record highs.

In Q4’24, the biggest CVC-backed rounds went primarily to AI companies. These include:

• AI search startup Perplexity’s $500M Series C, backed by Nvidia’s NVentures 
• Coding AI copilot Poolside’s $500M Series B, backed by the venture arms for Citigroup, HSBC, Capital One, LG, eBay, and Nvidia
• AI computing processor developer Lightmatter’s $400M Series D, backed by GV

CVCs are also investing in the energy companies powering the AI boom, such as Intersect Power, which raised the largest round at $800M (backed by GV).

Expect the trend to continue into 2025, as emerging AI markets mature further, such as AI agents & copilots for enterprise and industrial use cases; AI solutions for e-commerce, finance, and defense; and the computing hardware necessary to power these technologies.

The flight to quality continues

In 2024, the annual average deal size with CVC participation reached $27.3M, a 34% YoY increase and tied for the second highest level on record, exceeded only by the low-interest-rate environment of 2021.​

Median deal size also increased, though only by 8% to $8.6M.

Even though the number of CVC-backed deals declined in 2024, the increase in average annual deal size reflects a focus on companies with strong growth prospects. CVCs are prioritizing quality and committing more funds to a select group of high-potential investments.

Early-stage deals dominate

Early-stage rounds (seed/angel and Series A) made up 65% of CVC-backed deals in 2024, tied for the highest recorded level in more than a decade.​

In Q4’24, biotech companies were the early-stage fundraising leaders, accounting for 10 of the 20 largest early-stage deals. Biotech players City Therapeutics, Axonis, and Trace Neuroscience all raised $100M+ Series A rounds, with City Therapeutics and Axonis notably receiving investment from the venture arms of Regeneron and Merck, respectively.

Among all early-stage CVC-backed companies, the largest round went to Physical Intelligence, a startup focused on using AI to improve robots and other devices. Physical Intelligence raised a $400M Series A with investment from OpenAI Startup Fund.

Explore CVCs’ top early-stage company targets in Q4

CVC-backed funding plummets in Asia

Asia’s CVC-backed funding continued its downward trend in 2024, decreasing 34% YoY to $7B.

China was the main driver, with CVC-backed funding coming in at $0.5B or less every quarter in 2024.​ CVCs remain wary of investing in startups in the nation, which faces a variety of economic challenges, including a prolonged real estate slump, cautious consumer spending, strained government finances, and weakened private sector activity amid policy crackdowns.

In Japan, on the other hand, CVC activity remains robust. In 2024, funding with CVC participation ($1.7B) remained on par with the year prior, while deals (502) actually increased by 11%.

MORE VENTURE RESEARCH FROM CB INSIGHTS

• State of Venture 2024 Report
• State of Fintech 2024 Report
• State of Digital Health 2024 Report

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Venture funding surged past the $100B mark for the first time as AI infrastructure players pulled in billion-dollar investments. A wave of M&A deals and rapidly scaling AI unicorns further underscored the tech’s momentum.

Download the full report to access comprehensive data and charts on the evolving state of AI across exits, top investors, geographies, and more.

Key takeaways include: 

• Massive deals drive AI funding boom. AI funding hit a record $100.4B in 2024, with mega-rounds accounting for the largest share of funding we’ve tracked to date (69%) — reflecting the high costs of AI development. Quarterly funding surged to $43.8B in Q4’24, driven by billion-dollar investments in model and infrastructure players. At the same time, nearly 3 in 4 AI deals (74%) remain early-stage as investors look to get in on the ground floor of the AI opportunity. 
• Industry tech sectors lose ground in AI deals. Vertical tech areas like fintech, digital health, and retail tech are securing a smaller percentage of overall AI deals (declining from a collective 38% in 2019 to 24% in 2024). The data suggests that companies focused on infrastructure and horizontal AI applications are drawing greater investor interest amid generative AI’s rise.
• Outside of the US, Europe fields high-potential AI startup regions. While the US dominated AI funding (76%) and deals (49%) in 2024, countries in Europe show strong potential in AI development based on CB Insights Mosaic startup health scores. Israel leads with the highest median Mosaic score (700) among AI companies raising funding. 
• AI M&A activity maintains momentum. The AI acquisition wave remained strong in 2024, with 384 exits nearly matching 2023’s record of 397. Europe-based startups represented over a third of M&A activity, cementing a 4-year streak of rising acquisitions among the region’s startups. 
• AI startups race to $1B+ valuations despite early market maturity. The 32 new AI unicorns in 2024 represented nearly half of all new unicorns. However, AI unicorns haven’t built as robust of a commercial network as non-AI unicorns, per CB Insights Commercial Maturity scores, indicating their valuations are based more on potential than proven business models at this stage.
• Tech leaders embed themselves deeper in the AI ecosystem. Major tech companies and chipmakers led corporate VC activity in AI during Q4’24, with Google (GV), Nvidia (NVentures), Qualcomm (Qualcomm Ventures), and Microsoft (M12) being the most active investors. This reflects the strategic importance of securing access to promising startups while providing them with essential technical infrastructure.

We dive into the trends below.

For more on key shifts in the AI landscape in 2025, check out this report on the implications of DeepSeek’s rise.

Massive deals drive AI funding boom

Globally, private AI companies raised a record $100.4B in 2024. At the quarterly level, funding soared to a record $43.8B in Q4’24, or over 2.5x the prior quarter’s total. 

The funding increase is largely explained by a wave of massive deals: mega-rounds ($100M+ deals) accounted for 80% of Q4’24 dollars and 69% of AI funding in 2024 overall.

The year featured 13 $1B+ deals, the majority of which went to AI model and infrastructure players. OpenAI, xAI, and Anthropic raised 4 out of the 5 largest rounds in 2024 as they burned through cash to fund the development of frontier models. 

Overall, the concentration of funding in mega-rounds reflects the high costs of AI development across hardware, staffing, and energy needs — and widespread investor enthusiasm around the AI opportunity. 

But that opportunity isn’t limited to the largest players: nearly 3 in 4 AI deals (74%) were early-stage in 2024. The share of early-stage AI deals has trended upward since 2021 (67%) as investors look to ride the next major wave of value creation in tech.

CBI Customers: Track 15,000+ AI companies

Industry tech sectors lose ground in AI deals

Major tech sectors — fintech, digital health, and retail tech — are making up a smaller percentage of AI deals.

While the overall annual AI deal count has stayed steady above 4,000 since 2021, dealmaking in sectors like digital health and fintech has declined to multi-year lows. So, even as AI companies make up a greater share of the deals that do happen in these industries, the gains haven’t been enough to register in the broader AI landscape.

The data suggests that, amid generative AI’s ascendancy, AI companies targeting infrastructure and horizontal applications are drawing a greater share of deals. 

With billions of dollars flowing to the model/infra layer as well, investors appear to be betting that the economic benefits of the latest AI boom will accrue to the builders.  

Outside of the US, Europe fields high-potential AI startup regions

Although US-based companies captured 76% of AI funding in 2024, deal activity was more distributed across the globe. US AI startups accounted for 49% of deals, followed by Asia (23.2%) and Europe (22.9%). 

Comparing median CB Insights Mosaic scores (a measure of private tech company health and growth potential on a 0–1,000 scale) for AI companies that raised equity funding in 2024 highlights promising regional hubs. 

Explore 500+ high-potential AI startups

European countries dominate the top 10 countries by Mosaic score (outside of the US). Israel, which has a strong technical talent pool and established startup culture, leads the pack with a median Mosaic score of 700.

Overall activity on the continent is dominated by early-stage deals, which accounted for 81% of deals to Europe-based startups in 2024, a 7-year high.

The European Union indicated in November that scaling startups is a top priority, pointing to the importance of increased late-stage private investment in remaining competitive on the global stage.

AI M&A activity maintains momentum

The AI M&A wave is in full force, with 2024’s 384 exits nearly reaching the previous year’s record-high 397.

Acquisitions of Europe-based startups accounted for over a third of AI M&A activity in 2024. Among the global regions we track, Europe is the only one that has seen annual AI acquisitions climb for 4 consecutive years. Although the US did see a bigger uptick YoY (16%) in 2024, posting 188 deals. 

In Europe, UK-based AI startups led activity in 2024, with 32 M&A deals, followed by Germany (18), France (16), and Israel (12). 

Major US tech companies, including Nvidia, Advanced Micro Devices, and Salesforce, participated in some of the largest M&A deals of the year as they embedded AI across their offerings.

Search for recently funded AI companies with high M&A probabilities

AI startups race to $1B+ valuations despite early market maturity 

AI now dominates new unicorn creation. The 32 new AI unicorns in 2024 accounted for nearly half of all companies passing the $1B+ valuation threshold during the year. 

These AI startups are hitting unicorn status with much smaller teams and at much faster rates than non-AI startups: 203 vs. 414 employees at the median, and 2 years vs. 9 years at the median. 

CBI Customers: Dive into data on every unicorn

These trends reflect the current AI hype — investors are placing big early bets on AI potential. Many of these unicorns are still proving out sustainable revenue models. We can see this clearly in CB Insights Commercial Maturity scores. More than half of the AI unicorns born in 2024 are at the validating/deploying stages of development, while non-AI new unicorns mostly had to get to at least the scaling stage before earning their unicorn status.

Tech leaders embed themselves deeper in the AI ecosystem

In Q4’24, the top corporate VCs in AI (by number of companies backed) were led by a string of notable names: Google (GV), Nvidia (NVentures), Qualcomm (Qualcomm Ventures), and Microsoft (M12). 

As enterprises rush to harness AI’s potential, big tech, chipmakers, and other enterprise tech players are building their exposure to promising companies along the AI value chain.

Meanwhile, startups are linking up with these players to not only secure funding for capital-intensive AI development but also access critical cloud infrastructure and chips.

MORE AI RESEARCH FROM CB INSIGHTS

• What DeepSeek’s model releases mean for the future of AI
• Here’s how leading strategy teams are successfully driving generative AI adoption in their organizations
• The foundation model divide: Mapping the future of open vs. closed AI development
• 15 tech trends to watch closely in 2025
• Inside the AI drug discovery arms race: Record M&A activity, a biologics funding spree, and more
• The industrial AI agents & copilots market map

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

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But beyond the momentum building in AI, global deal activity plunged 19% YoY to its lowest level since 2016, creating both challenges and opportunities for investors and corporate strategists.

Download the full report to access comprehensive data and charts on the evolving state of venture across sectors, geographies, and more.

Key takeaways from the report include:

AI is eating VC. In 2024, AI represented 37% of venture funding and 17% of deals — both all-time highs. AI infrastructure players raised all of the top 5 venture deals of the year, with 4 closing in Q4’24 alone — driving a 2-year high in quarterly funding. With nearly 3 in 4 (74%) AI deals being early-stage in 2024, investors are staking out early claims to reap the rewards of the tech’s potential.

Aside from AI, venture dealmaking is in a drought. Globally, deal activity fell 19% YoY to 27K in 2024 — its lowest annual level since 2016. The drop was most pronounced in countries like China (-33% YoY), Canada (-27%), and Germany (-23%). However, several countries in Asia — Japan, India, and South Korea — have bucked the downward trend. Their resilience suggests attractive investment conditions.

AI and industrial automation are common themes among the fastest-growing tech markets. Out of 1,400+ tech markets that CB Insights tracks, those with the highest rate of YoY deal growth include enterprise AI agents, genAI for customer support, industrial humanoid robots, and autonomous driving systems. Expect these technologies to continue maturing in 2025, increasing their disruptive potential.

Despite market uncertainty, early-stage valuations hit a record-high median of $25M in 2024. Investors are packing into early-stage rounds to ride the next major wave of value creation in tech, likely drawn by startups’ ability to now build products with less capital and fewer people thanks to AI tools and infrastructure. However, early-stage startups could face a reality check when they try to raise later-stage rounds if they have yet to prove they can sustain growth. Although mid- and late-stage deal valuations rebounded slightly vs. 2023, they remain muted compared to 2021 and 2022.

IPO timelines get delayed. From first funding to IPO, VC-backed companies that went public in 2024 waited a median of 7.5 years — 2 years longer than in 2022. Amid unfavorable market conditions, some late-stage players like Stripe and Databricks have resorted to raising additional equity funding or selling private shares in lieu of going public. This allows them to create liquidity for early investors and employees when the path to a public debut is rocky.

We dive into each trend below.

AI is eating VC

The 5 largest deals of the year all went to AI model and infrastructure players (led by Databricks’ $10B Series J, followed by a $6.6B round for OpenAI, two $6B rounds for xAI, and a $4B round for Anthropic). But the activity isn’t limited to the largest, most well-resourced AI players. 

Across the board, AI companies are capturing a higher share of deal volume — nearly one in 5 deals (17%) now go to AI companies, almost triple the share from 2015 (6%). AI deal volume remained above 4,000 for the fourth year in a row. 

CBI customers: Track 15,000+ AI companies

The boom is providing tailwinds for every stage of the startup lifecycle, from early-stage companies — which take 3 out of 4 deals in AI — to startup exits. The AI M&A wave is in full force, with 2024’s 384 exits nearly rivaling the previous year’s record-high 397.

This trend will continue in 2025 as incumbents look to grab AI tech and talent and build end-to-end AI offerings. Get the full breakdown of what AI M&A means for corporate strategy in our Tech Trends 2025 report.

In Q4’24, the AI boom helped fuel a substantial rebound in global funding. The quarter’s funding tally reached $86.2B — a 2-year high, and an increase of 53% quarter-over-quarter (QoQ).

60% of that quarterly total, or $52B, came from mega-rounds (deals worth $100M+) — nearly tying Q1’21 (61%) for the highest share ever across venture. 

At the same time, quarterly deal volume steadily declined throughout 2024, including slipping below 6,000 in Q4’24 for the first time since 2016.

Aside from AI, venture dealmaking is in a drought

Despite AI’s surge, most venture sectors face their worst dealmaking drought in nearly a decade, forcing investors to adjust their strategies. Many investors are taking a more selective and risk-off approach right now as they wait out macroeconomic volatility and geopolitical tensions.

Among major dealmaking countries and regions (those seeing 500+ deals per year), the slump was most pronounced in China (-33% YoY drop in deals), Canada (-27%), and Germany (-23%). 

However, several countries in Asia bucked the trend and notched slim YoY gains: Japan (+2%), India (+1%), and South Korea (+1%). These countries have invested heavily in developing their startup ecosystems and may be benefiting indirectly from investors diverting funds away from China.

AI and industrial automation are common themes among the fastest-growing tech markets

AI and industrial automation are at the center of some of the fastest-growing markets in tech.

We filtered CB Insights’ 1,400+ tech markets for those with at least 20 equity deals over the last 2 years, then singled out those with the strongest deal growth YoY in 2024.

The enterprise tech and industrials sectors dominate, comprising 9 of the top 10 tech markets. Advancements in generative AI are fueling much of the activity in areas like humanoid robots and autonomous driving systems. Investors are also backing tech companies improving industrial processes like water treatment and purification, with deals to the market more than doubling YoY.

The enterprise tech and industrials sectors are also seeing a wave of hiring, as they lead in YoY headcount growth among all sectors. Industrials markets saw an average of 11% headcount growth last year, followed by enterprise tech markets with 10%. 

Financial services and the consumer & retail industries are noticeably absent from the top 10 fastest-growing markets. Given the tough venture landscape, emerging technologies in these areas face an uphill battle.

CBI Market Index: Compare 1,400+ markets

Early-stage deals are showing strength

Globally, early-stage dealmaking represents one of the most vibrant areas of venture right now, with median deal size and valuation reaching all-time highs in 2024.

The seed/angel and Series A stages remain resilient despite the broader downturn, in part because investors view them as a safe haven to ride out late-stage challenges like constricted exit opportunities and capital constraints. Deal sizes and valuations for the mid- and late stages rebounded slightly vs. 2023 but were muted when compared to the boom times of 2021 and 2022.

Corporate strategy and development teams seeking out early-stage opportunities can see 900+ high-potential startups here. To identify these players, we looked at the nearly 11,000 VC-backed startups that raised seed or Series A rounds in 2024, then filtered for those with the healthiest businesses (600+ Mosaic score) and strongest management teams (600+ Management Mosaic score).

Explore 900+ high-potential early-stage startups

IPO timelines get delayed

Most tech firms continue to shirk the IPO market. Some are still waiting for macroeconomic conditions to stabilize, while others prefer to focus on topline growth without having to deal with the financial scrutiny that comes with being a public company.

This is pushing back the timelines for IPO-ready companies even further. 

From first funding to IPO, VC-backed companies that went public in 2024 waited a median of 7.5 years — 2 years longer than in 2022.

While Q4’24 saw an uptick in global IPOs, activity remains down vs. historical levels. In the current climate, many late-stage startups will likely opt instead to raise more private funding to sustain operations and pay out employees or early investors.

Search for recently funded companies with high IPO probabilities

Related resources from CB Insights:

• Live briefing on venture trends for 2025
• All AI research from CBI
• 15 tech trends to watch closely in 2025
• Game Changers 2025: 9 technologies that will change the world
• $1B+ Market Map: The world’s 1,249 unicorn companies in one infographic

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