After divesting its logistics business in 2023, the company refocused on its core strength: powering commerce infrastructure. Since then, Shopify has accelerated its growth through targeted partnerships, acquisitions, and product development — growing its share of the US e-commerce market from 10% to 12% and boosting revenue by 26% in FY2024. 

Now, Shopify is primed to take on new challenges. From enabling immersive shopping experiences to onboarding enterprise clients and monetizing its data through advertising, the company is laying the foundation for a more ambitious role in global commerce.

Drawing on CB Insights data across investments, acquisitions, integrations, and earnings transcripts, we identify 3 key areas that reveal where Shopify is heading next:

• Powering immersive and unified shopping experiences: Shopify’s relationships with gaming, payments, and agentic commerce players will enable always-on, cross-platform shopping — with Shopify infrastructure at the ecosystem’s core.   
• Becoming the go-to enterprise commerce platform: Through system integrator partnerships, composable solutions like Commerce Components, and unbundled tools like Shop Pay, Shopify is positioning itself as a modular alternative to Salesforce and Adobe.
• Turning customer data into new ad revenue streams: With proprietary tools like Shopify Audiences and new integrations with CDPs and campaign platforms, Shopify is laying the groundwork for a retail media network — creating new ways to monetize merchant and shopper data at scale.

In the graphic below, we show where Shopify has already built momentum across its three strategic pillars — and where we think it’s heading next, including our predictions on future partners and acquisitions.

These priorities signal how the e-commerce giant could reshape buying experiences and challenge established players across advertising, enterprise software, and commerce infrastructure.

We dive into each prediction below. 

1. Powering immersive and unified shopping experiences.

Shopify’s growing US e-commerce share reflects a deliberate strategy to embed commerce capabilities into more contexts. Its integrations with platforms like Roblox and Perplexity AI suggest a vision of always-on, channel-agnostic shopping where Shopify is the core infrastructure across both traditional and emerging environments.

Enabling shopping at any time, on any platform

In late 2024, Shopify took a step into the world of agentic commerce by integrating with Perplexity’s new AI shopper, Buy with Pro. This has enabled consumers to browse and transact directly via Shop Pay within Perplexity’s interface. 

Around the same time, it became Roblox’s first commerce integration partner, giving Shopify merchants access to 80M+ daily users through in-game storefronts powered by Shopify Checkout.

Source: CB Insights — Shopify Q3’24 earnings call

To that end, Shopify is expanding the functionality of its own products. For example, in 2024, it introduced “tap to pay” for its Point of Sale (POS) app and introduced offline payment capabilities, reinforcing its commitment to connecting online and physical experiences. Its integration with loyalty platform Gatsby enables merchants to engage customers across both environments.

Meanwhile, its partnership with India-based Cashfree Payments — enabling local on-site card processing — is part of a broader effort to tap into local economies through regional POS providers.

Using CB Insights’ Mosaic score, which measures business momentum, we sorted early- and mid-stage POS companies in a few key markets (EU and APAC) where Shopify could expand. Focusing on companies that serve retailers, we surfaced these 3 potential partners:

• Flatpay (Mosaic: 783) is a Danish company offering simplified payment processing solutions for small and medium-sized businesses. 
• Teya (Mosaic: 758), based in London, provides payment processing and financial services for small and medium-sized businesses across Europe. 
• Dtcpay (Mosaic: 735) is a Singapore-based digital payment platform. Its solution includes multi-currency swaps to convert fiat and stablecoins. 

Get the full list of potential partners in the EU and APAC

2. Becoming the go-to enterprise commerce platform.

Shopify has built the foundation to move beyond its traditional small-business customer base and compete directly with enterprise commerce platforms like Salesforce Commerce Cloud and Adobe Commerce. The company is positioning itself as a modular, flexible infrastructure layer — designed to meet the needs of large, complex merchants.

Partnerships with migration solutions clear a big hurdle

One of the biggest barriers for enterprise merchants is the complexity of migrating from legacy platforms. To address this, Shopify has steadily expanded its network of system integrators (SIs) since 2022, forming partnerships with Deloitte, EY, and KPMG to streamline onboarding and implementation.

Source: CB Insights — Shopify Q3’23 earnings call

In April 2024, Shopify deepened this strategy with a joint partnership alongside Google Cloud and Cognizant to offer end-to-end digital commerce solutions. These alliances signal Shopify’s increasing traction among enterprise IT buyers — and the company’s evolving go-to-market motion.

Shopify has also added specialized migration and enablement partners to its app store. In August 2024, it onboarded Pivotree, a digital commerce design firm, and in January 2025, expanded its relationship with Anatta to support enterprise migration needs.

Streamlining checkout and payments for large merchants

Simplifying payment workflows remains a core part of Shopify’s enterprise pitch. Its a la carte checkout solution, Shop Pay, is now offered independently and has been adopted by large brands like Coach. Shopify has layered on key partnerships to support broader payment functionality:

• In June 2023, it partnered with Adyen to enable more efficient processing for global enterprise merchants.
  
• In September 2024, it expanded its integration with PayPal, making it a card processor for Shopify and streamlining order management, reporting, and chargebacks.

Shopify has also supported crypto payments via its app store. In 2024, Solana Pay — powered by Helio (now owned by MoonPay) — added support for more tokens, loyalty programs, and stablecoin conversion, expanding Shopify’s optionality for cutting-edge payment rails.

The company is also offering other point solutions to serve enterprise merchants’ needs. In October 2024, it partnered with AI search company Coveo to offer tools for AI-driven product discovery, personalized recommendations, and more, focusing on more prominent retailers.

Learn more about companies using generative AI in e-commerce

Its integrations with tax technology leaders Vertex and Avalara further support its enterprise expansion, enabling complex compliance for cross-border transactions.

Source: CB Insights — Shopify business relationship insights

The tax compliance software market offers Shopify more potential tax compliance partners as it expands its reach with enterprise customers. Using the market’s ESP, which identifies and ranks leading private companies in a given technology landscape, we can highlight challenger companies on the rise that could be valuable relationships for Shopify:

• Sovos provides global tax compliance and regulatory reporting software solutions. 
• Exactera offers AI-powered tax compliance solutions for transfer pricing, income tax provision, and R&D tax credits.
• Neo.Tax also builds AI-powered tax automation software for startups and small businesses.

These moves underscore Shopify’s shift toward a composable, enterprise-grade stack — built to compete with legacy vendors by offering faster implementation, flexible tooling, and global readiness.

3. Shopify will use its reach and first-party data to power advertising for its merchants.

Shopify has long equipped its merchants with tools for personalization and customer acquisition. But its recent product upgrades and tech partnerships point to a broader ambition: turning its vast merchant network and rich first-party data into a full-fledged advertising business.

The activity hints at Shopify building its own version of a retail media network—one that could allow the company to sell ad space to merchants and outside brands, putting it in competition with advertising leaders like Amazon, Google, and Walmart.

To start, Shopify has expanded access to 2 of its own ad-focused products:

• The newest iteration (v2.4) of its customer acquisition tool, Shopify Audiences, launched in June 2024, helps merchants target narrower customer groups and maximize ad performance across networks and platforms. Some merchants have seen CAC reductions of up to 50%. 
• In December 2024, the company made its advertising tool, Shop Campaigns, available to all merchants in the US and Canada. Previously, only higher-tier Shopify Plus merchants could use the product. 

But Shopify’s leadership sees potential in advertising for Shopify beyond its proprietary products:

Source: CB Insights — Shopify Q1’24 earnings call

To unify and activate customer data, Shopify has partnered with third-party platforms that aggregate behavioral and transactional insights:

• In October 2024, Blueshift made its solution available on the Shopify app store. Its tools include a customer data platform, automated decision-making for recommendations, and a cross-channel marketing platform.
• Also in October 2024, Trellis announced an integration with Shopify. The relationship integrates shopper data into Amazon Marketing Cloud, connecting shopper insights across platforms to more effectively target messaging. 

Looking ahead, Shopify may deepen its capabilities in data orchestration by offering its own customer data platform (CDP) or data clean room solution. We ranked the companies in the CDP market by their M&A probability and Mosaic score (600+) to isolate potential M&A targets for Shopify:

• Optimove leverages AI to orchestrate personalized multichannel campaigns for B2C companies.
• Simon specializes in personalization and customer journey orchestration for retail, travel, and subscription businesses. 
• Hightouch is a composable customer data platform specializing in data activation and reverse ETL services.

Shopify is also building new demand channels for merchants. In 2024, it partnered with Mirakl to enable third-party marketplace creation and with Target to feature Shopify merchant products on the retailer’s digital shelves.

These moves suggest Shopify is building more than merchant tools — it’s assembling a vertically integrated commerce and media stack that could challenge the dominance of legacy ad platforms and redefine how brands connect with shoppers.

Research: How generative AI could supercharge retailers’ ad networks

RELATED RESEARCH FROM CB INSIGHTS:

• The future of the customer journey: AI agents take control of the buying process
• How generative AI could supercharge retailers’ ad networks
• 7 tech M&A predictions for 2025
• Interviews with Shopify customers

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M&A is back.

Below, we break down what’s driving the surge in deals, then zoom in on Nvidia’s latest purchase.

Buyers on the prowl

Q1’25 has already seen 11 $1B+ deals for VC-backed companies worth a combined $54.5B — blowing past quarters out of the water.

More than half of that value comes from Google’s $33B purchase of Wiz, the biggest VC-backed M&A exit of all time.

It’s not just tech startups — consumer & retail brands are getting snapped up too, like Pepsi’s $2B acquisition of Poppi.

But tech is leading the charge.

M&A activity in the sector rebounded 5% in 2024 and we expect it to gain more steam this year thanks to several factors:

• • Less regulatory pressure: Big tech players like Google are betting on a friendlier dealmaking climate with Lina Khan out as head of the FTC.
  • AI boom: Incumbents are anxious to get their hands on AI assets and infrastructure (see ServiceNow’s acquisition of MoveWorks and SoftBank’s acquisition of Ampere). 
  • Cheaper prices: Tech M&A valuations keep falling, encouraging strategic and financial buyers to get off the sidelines.

Nvidia’s M&A playbook

Among the Mag 7, Nvidia stands out for its aggressive acquisition strategy.

All told, Nvidia has snapped up 7 AI startups since 2021, with 4 of these in just the last year.

Last week it bought Gretel — reports place the exit valuation north of $320M (Gretel’s last disclosed valuation) but less than $1B.

Per CB Insights’ ESP ranking, Gretel is a leader in the synthetic training data market. 

Source: CB Insights — ESP ranking of players in tabular and text-based synthetic training data

Synthetic data offers a potential solve to 3 issues in AI development:

• A diminishing pool of high-quality text data to train more advanced LLMs.
• The need to preserve privacy by using anonymized data, critical to AI adoption in industries like healthcare and finance.
• The absence of real-world data to train physical AI models on tasks like driving cars or piloting humanoid robots.

CBI customers can see our analysis of 50 synthetic data providers here. 

By acquiring Gretel, Nvidia positions itself at the forefront of the synthetic data market and strengthens its position in emerging areas like physical AI.

Nvidia sees the physical domain as the next evolution of AI, according to CB Insights’ earnings call transcripts.

Source: CB Insights — Nvidia Q4 FY 2025 earnings transcript

Back in June 2024, we wrote about how Nvidia is investing in and partnering with companies focused on industrial applications, like digital twins and robotics, which can rely on AI for simulation and training.

See where else the $3T company is targeting growth in our Nvidia strategy map.

Related research from CB Insights:

• Analyzing Nvidia’s growth strategy: How the chipmaker plans to usher in the next wave of AI
• State of Venture 2024 Report
• 7 tech M&A predictions for 2025
• Generative AI is accelerating the timeline for fully autonomous driving

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

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According to CB Insights headcount data, AI firms such as Glean, Scale, and OpenAI have increased their workforce in the country by as much as 67% over the last six months. The country’s domestic AI companies have also seen 32% headcount growth over the same period.

Notably, India is now OpenAI’s second-largest market — with a user base that tripled in the past year — while global tech giants like Microsoft and Nvidia have made substantial infrastructure investments in the country.

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The AI boom has set the stage for a wave of tech M&A this year.

After 2 consecutive years of decline, tech M&A deals were up in 2024, with some of the largest deals centering on AI. AI companies have also bucked the general downward trend in exit valuations, instead seeing nearly double the median acquisition price from 2023 to 2024.

Using CB Insights’ predictive signals, such as Mosaic and M&A Probability, we’ve identified 7 AI-related areas where we expect to see M&A activity this year, as well as high-potential acquisition targets for each.

See highlights below, and download the full report for the rationale behind each prediction, as well as M&A target shortlists.

Tech M&A prediction highlights

• Big tech players set their sights on humanoid robotic: As physical AI takes off thanks to the rise of LLMs, humanoid robotics is becoming big tech’s next battlefield. Among high-potential acquisition targets, 1x stands out for its dual focus on industrial and consumer humanoids (just in January, it acquired Kind Humanoid to accelerate household robot development). This makes it a prime target for Meta, which recently announced plans to enter the consumer humanoid market.
• Enterprise tech heavyweights compete for AI infrastructure dominance: We’re already seeing strong signals from cash-rich companies such as Cisco and IBM, which are future-proofing their business models with AI investments. Hardware-aware AI optimization players CentML and Nota AI — which help accelerate AI model deployment while reducing compute costs — appear in our AI infrastructure acquisition target list. These companies have already shown quantifiable efficiency improvements as well as validation from Nvidia as a partner or investor.

Source: CB Insights advanced search. Data is dynamic (as of 2/27/2025).

• Data center energy demands fuel interest in cooling tech: Companies offering immersion and liquid cooling solutions enjoyed a funding rebound last year, attracting a combined $120M in fresh funding. Hypertec and Submer are high-potential acquisition targets in this space.
• Professional services firms seek AI capabilities: GenAI is coming for knowledge jobs — and leading professional services firms are buying AI capabilities to get ahead of it. One area where we see high M&A potential for professional services firms is to cater to clients’ responsible AI needs, with potential acquisition targets such as Lasso Security and HydroX AI.
• Pharma companies target AI drug discovery startups: AI drug discovery M&A is surging, with 12 deals in the sector since 2023. That M&A deal volume reflects both a maturing technology and growing urgency among pharma players to bring AI tech in-house.
• SaaS giants fortify their offerings with AI agent acquisitions: While some believe AI agents signal the death of SaaS companies, we anticipate SaaS leaders will acquire AI agent companies to avoid disruption. We’re already starting to see this happen with ServiceNow acquiring Moveworks for close to $3B in March 2025.

Source: CB Insights — ServiceNow Acquisition Insights

• Coding AI agents drive next wave of AI agent consolidation: Explosive growth, soaring valuations, a fractured AI agent landscape, and rising doubts about revenue defensibility make the coding AI agents market ripe for consolidation. While some players like Cursor look too expensive for an acquisition, we’ve identified Warp, Vidoc, and Bito as likely targets with high Mosaic scores and higher-than-average M&A Probabilities.

What is Mosaic?

Mosaic is CB Insights’ proprietary metric that measures the overall health and growth potential of private companies using non-traditional signals. Mosaic is widely used as a target company and market screener to identify high-potential emerging tech companies, typically defined as those with a score of 510 or higher.

What is M&A Probability?

M&A Probability is CB Insights’ proprietary signal that measures a private company’s chance of an M&A exit within the next 2 years. It is used to quickly screen and triangulate companies based on exit likelihood.

Combining both Mosaic Score and M&A Probability makes it easy to shortlist acquisition targets.

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As AI agents dominate the conversation, customers are growing skeptical about whether they can live up to the hype.

In March, we’ve interviewed 40+ customers of AI agent products and are hearing of 3 primary pain points right now:

1. Reliability
2. Integration headaches
3. Lack of differentiation

1. Reliability

This is the #1 concern raised by organizations adopting AI agents, with nearly half of respondents citing reliability & security as a key issue in a survey we conducted in December. 

According to CBI’s latest buyer interviews, AI agent reliability varies dramatically across providers. Many customers report a gap between marketing and reality.

“Whatever was promised didn’t work as great as said,” one LangChain user told us about the company’s APIs. “We encountered cases where we were getting partially processed information, and the data we were trying to scrape was not exactly clean or was hallucinating.”

For many customers, reliability is largely a function of how complex the data and use cases are. For instance, the LangChain customer saw ~80% accuracy for simpler tasks, but “for complex tasks, the accuracy dropped to around 50%.” 

Organizations are tackling the reliability issue with 1) human oversight; and 2) more extensive model training.

An Ema customer, for instance, first has a subject-matter expert review outputs, and once “more than 90% of the responses that we have tested are now accurate, we let it fly.”

A customer for CrewAI, which orchestrates teams of AI agents into “crews,” takes an even more involved approach:

The customer still needs to intervene with their own ML algorithms when CrewAI is unable to handle outliers or unconventional data structures. If CrewAI is able to tackle these cases in the future, “that would be a huge leap forward.” 

Source: CB Insights — AI agent market map featuring CrewAI and LangChain in the infrastructure category 

2. Integration headaches

Integration limitations rank as another top customer pain point.

For one, lack of interoperability poses long-term challenges, as this Cognigy customer notes:

An Artisan AI customer echoes this: “It was a bit of a gamble that we were signing up for a product where they didn’t have quite all the integrations that we wanted.”

Where customers see real value from these tools is when they can support seamless data flow, especially through their existing tech stack. This buyer went with Decagon because of its integrations:

3. Lack of differentiation

More than half of private capital flowing into the AI agent space has gone to horizontal applications — but these markets, like customer support and coding, are becoming highly saturated.

“There’s so many short-term moats, but in the long term there is no moat,” one customer observed. “Whatever you build will be rapidly reproduced.”

In a crowded market, specialization will determine success.

Hebbia, for instance, has tailored its solution to financial players. An exec at a PE firm framed this as a selling point when getting internal buy-in: “When I bring tools to the deal team that live and breathe diligence and deal execution, ensuring that it’s aligned to what they know and understand and [that it] speaks their language is incredibly important.”

While many horizontal AI agents are actively deploying or even scaling their solutions, vertical AI agents remain nascent, with half still in the first 2 levels of Commercial Maturity. 

They’ll gain more momentum this year as enterprises prioritize solutions that are highly tailored to the needs of individual industries. 

CB Insights customers can read our latest interviews with AI agents’ customers here.

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Clinical development represents one of pharma’s costliest and riskiest investments.

Trials average $55M each, per a study in JAMA Health Forum, and can take more than a decade to complete. However, over 90% of drugs still fail. AI is emerging as a game-changing force in clinical development, tackling its biggest pain points head-on.

Want to see more research? Join a demo of the CB Insights platform.

If you’re already a customer, log in here.

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Small teams are getting big payouts.

That’s what the M&A data for 2025 says.

Using CB Insights M&A transaction and headcount data for Q1’25 so far, we found that tech companies acquired for $100M or more had just 100 employees at the median.

Our analysts dove into the tech M&A landscape in a live briefing on March 18 — download the recording here.

We zoomed in on the companies exiting with teams of 100 employees or under, and they’re typically:

• young (7 years old on average)
• bootstrapped (a majority have raised under $20M in equity funding)

See the top 10 by valuation-to-employee ratio below.

CBI customers can explore these 10 startups here.

The top exit by that metric went to Voyage AI, which offers embedding models and ranking tools to improve AI search and retrieval.

With just 19 employees and a price tag of $220M — up 2x since its funding round last September — Voyage AI’s sale to MongoDB equated to $11.6M per employee.

Bon voyage

For MongoDB, Voyage AI represents an opportunity to own more of the AI development process and build customer trust, specifically around output reliability.

Source: CB Insights — MongoDB Q4 FY 2025 earnings call

This is one of the main hurdles to broader AI adoption.

In a December 2024 survey we conducted on AI agents — the clear next evolution for enterprise genAI deployment — nearly half (47%) of respondents cited reliability & security as a top obstacle.

To address this concern, platforms that help businesses organize, maintain, and leverage their data effectively will become even more important.

Acquisition radar

MongoDB isn’t the only one acquiring AI startups to stitch together more unified AI development tools.

Data management giants Databricks and Snowflake have been on AI acquisition sprees, acquiring 5 AI startups a piece since 2023 — more than any other acquirers globally.

The question is: Who’s next?

We expect the next wave of AI M&A targets to be those building out AI agent infrastructure.

Drilling down further, there are 47 startups with teams of 100 employees or less.

The most likely M&A targets, ranked using CB Insights’ Exit Probability, are:

• Letta (agent memory)
• Coval (agent evaluation & observability)
• Fixie (voice AI)

Source: CB Insights — Platform search of AI agent infrastructure startups

Another top contender is Unstructured, in the data curation space — the company has received previous backing from the venture arms of both MongoDB and Databricks.

Customers can unlock the full list of AI agent infra targets here.

RELATED RESEARCH FROM CB INSIGHTS:

• Tech M&A Predictions for 2025
• Databricks wants to be a one-stop shop for AI. Here’s how it plans to get there
• Our 6 predictions for the insurance space in 2025
• State of Venture 2024 Report

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Now, the strategic question for insurers isn’t whether to adopt generative AI but how quickly.

We’ve developed 6 predictions — informed by CB Insights datasets, including financing and acquisition data, Business Relationships, Earnings Transcripts, and Exit Probability — that we think will guide competitive dynamics over the coming year:

Want to see more research? Join a demo of the CB Insights platform.

If you’re already a customer, log in here.

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Estimates indicate that US hospitals lose $262B annually to revenue cycle inefficiencies, while drugmakers spend more than $1B on average to develop a single drug. Meanwhile, the healthcare workforce in the US faces high burnout and a projected shortage of 124,000 physicians by 2034, according to the Association of American Medical Colleges.

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While AI copilots have already made inroads across industries, the next evolution — autonomous agents with greater decision-making scope — is arriving quickly. AI agent startups raised $3.8B in 2024 (nearly tripling 2023’s total), and every big tech player is already developing AI agents or offering the tooling for them.

Implications for enterprises will be far-reaching, from altering workforce composition (with new hybrid teams of humans and AI agents) to maximizing operational efficiency through full automation of routine tasks. 

Below we identify 170+ promising startups developing AI agent infrastructure and applications. 

CBI customers: Track 250+ AI agent companies

We selected companies for inclusion based on Mosaic health scores (500+) and/or funding recency (since 2022). We included private companies only and organized them according to their primary focus. This market map is not exhaustive of the space.

Want to be considered for future AI agent research? Brief our analysts to ensure we have the most up-to-date data on your company. 

Outlook on AI agents

Fully autonomous agents remain limited due to issues pertaining to reliability, reasoning, and access. Most agent applications today operate with “guardrails” — within a constrained architecture where, for example, the LLM-based system follows a decision tree to complete tasks. 

Agents featured on this map include some combination of the following components: 

• Reasoning: Foundation models that enable complex reasoning, language understanding, and decision-making. These models evaluate information and form the cognitive core of the agent.
• Memory: Systems that store, organize, and retrieve both short-term contextual information and long-term knowledge.
• Tool use: Integration capabilities that allow agents to interact with external applications, APIs, databases, the internet, and other software. 
• Planning: The agent’s architecture for breaking down complex tasks into more manageable steps, reflecting on performance, and adapting as necessary.  

We expect more startups to move up the scale of autonomy as AI capabilities advance. Improvements in reasoning and memory will enable more sophisticated decision-making, adaptability, and task execution.

For example, in September 2024, legal AI startup Harvey announced that OpenAI’s o1 reasoning model, supplemented with domain-specific knowledge and data, was enabling it to build legal agents. The company, which raised $300M at a $3B valuation in February 2025, has doubled its sales force in the last 6 months, indicating rising market demand.

While the above market map highlights the private landscape (with a focus on enterprise applications), tech giants and incumbents are also launching agents. We predict big tech and leading LLM developers will own general-purpose AI agents, but there are many opportunities for smaller, specialized players. 

Looking ahead, watch for new form factors outside of the copilot/chatbot interface that will push the boundaries of what an “agent” is. Early indications of this include “AI-native” workspaces — tools and platforms built from the ground up around AI capabilities, rather than layering AI features on top of a traditional product. For instance:

• Eve’s legal platform aims to automate aspects of the whole case lifecycle (from case intake to drafting). 
• Hebbia’s Matrix product builds spreadsheets that mine information from files (in rows) and deliver answers to questions (in columns), proactively discovering, organizing, and surfacing data.
• With its Dia product, The Browser Company is exploring web browsing interfaces that can summarize content, automate repetitive web tasks, and even anticipate next actions.

Category overview

AI agent infrastructure

This segment covers companies building agent-specific infrastructure. (We excluded general genAI infrastructure markets like foundation models and vector databases from the map.)

Development tools

A diverse ecosystem of tools has emerged to support agents’ development. These range from memory frameworks like Letta that enable persistent, retrievable memory across interactions; to tools that allow agents to take action via integration (e.g., Composio), authentication (e.g., Anon), and browser automation (e.g., Browserbase).

Another set of companies is giving agents more utility across payments (which includes companies developing crypto wallets for agents as well as virtual cards) and voice (development platforms and tools for testing AI voice applications as well as speech models).

Meanwhile, demand for simplified, comprehensive deployment options is driving the rise of AI agent development platforms — the most crowded infrastructure market on our map. 

LLM developers including Cohere (with its North AI workspace) and Mistral have launched their own agent development frameworks, while Amazon, Microsoft, Google, and Nvidia all offer AI agent development tooling. With many enterprises favoring established vendors due to lower risk, big tech companies have significant advantages here.

Trust & performance

Concerns around reliability and security have helped establish a market for agent evaluation & observability tools. Early-stage companies are targeting applications such as automated testing (e.g., Haize Labs) and performance tracking (e.g., Langfuse). 

Multi-agent systems, where specialized sub-agents work together to complete tasks, also show promise in improving accuracy. Insight Partners-backed CrewAI’s multi-agent orchestration platform is reportedly already used by 40% of the Fortune 500. 

Vendors are also tackling reliability concerns directly. Based on our briefings with 20+ AI agent startups in Q1’25, companies are using 5 primary methods to build user trust: 

1. Transparency
2. Human oversight
3. Technical safeguards
4. Security & compliance
5. Continuous improvement 

Horizontal applications & job functions

Horizontal AI agent startups make up nearly half of the map and overall landscape. 

This segment primarily features startups targeting enterprises, with industry-agnostic applications across job functions like HR/recruiting, marketing, and security operations. Companies in the productivity & personal assistants market, including OpenAI with its Operator agent, are targeting consumers and employees directly.  

The AI agent markets with the most traction — based on companies’ median Mosaic health scores — are customer service and software development (which includes coding and code review & testing agents). These markets are also among the most crowded due to the value agents bring to well-defined workflows and testable environments. 

We see this reflected in adoption, particularly at the customer service layer: Among 64 organizations surveyed by CB Insights in December 2024, two-thirds indicated they are using or will be using AI agents in customer support in the next 12 months. 

Overall, horizontal AI agent applications are more commercially mature compared to the infrastructure and vertical segments, with over two-thirds of the market deploying or scaling their solutions based on CBI Commercial Maturity scores. 

Vertical (industry-specific) applications

We expect increasing verticalization as startups carve out niches by solving industry-specific customer problems, especially in areas with strict regulatory scrutiny and data sensitivity.

This category features companies catering to industries including: 

• Financial services & insurance: The most crowded vertical category on the map with 11 companies, startups here are targeting a variety of finserv workflows such as financial research (Boosted.ai and Wokelo), insurance sales & support (Alltius and Indemn), and wealth advisory prospecting & operations (Finny AI and Powder). 
• Healthcare: Solutions in this market aim to reduce the volume of manual tasks for healthcare professionals across use cases like clinical documentation, revenue cycle operations, call centers, and virtual triage. Solutions from companies like Thoughtful AI (revenue cycle operations) and Hippocratic AI (staffing marketplace) are targeting end-to-end healthcare workflows. 
• Industrials: These companies look to optimize processes and equipment — including control systems, robots, and other industrial machines — without relying on consistent human intervention. For example, Composabl launched an agent platform in May 2024 that uses LLMs to create skills and goals for agents that can control industrial equipment. Public companies like Palantir are also active in this space. Learn more in our industrial AI agents & copilots market map. 

RELATED RESEARCH

• What’s next for AI agents? 4 trends to watch in 2025
• The enterprise AI agents & copilots market map
• The Multi-Agent AI Outlook
• Future of the workforce: How AI agents will transform enterprise workflows

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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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These LLM-based systems mark an evolution beyond copilots: AI agents can accomplish complex tasks on a user’s behalf with minimal intervention, from sales prospecting to compliance decisioning. 

In the rapidly growing landscape for agent infrastructure and applications, over half of companies in the market have been founded since 2023. Meanwhile, funding to startups in the space nearly 3x’d in 2024.

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Imagine: your personal AI agent notifies you that a hair dryer you’ve been eyeing is now on sale. The product page highlights benefits tailored to your curly hair, while the agent confirms it will arrive before your upcoming trip.

With your approval, the agent handles the purchase through your secure wallet. Later, it proactively suggests complementary hair care products for the summer season.

This world of autonomous commerce isn’t as far off as it seems. Tech and e-commerce leaders — including OpenAI, Nvidia, Amazon, Walmart, Google, and Apple — are already building AI systems that are steps away from conducting transactions. 

AI agents will impact each stage of the customer journey, streamlining the path to purchase and fundamentally transforming how businesses build relationships with consumers and drive loyalty.

We use CB Insights data on early-stage fundraising, public companies, and industry partnerships to analyze how generative AI — especially AI agents — is transforming the customer journey.

In the 11-page report, we cover 3 predictions that emerged from our analysis: 

1. First-party transaction data will shape the future of AI-driven personalization. As personalization becomes more sophisticated at the awareness and consideration stages, companies with direct access to first-party data will have an edge.
2. Direct-to-agent (D2A) commerce will kill traditional loyalty. With AI agents handling browsing and shopping, traditional loyalty programs will lose effectiveness as agents optimize shopping across a select group of merchants.
3. A few AI agents will own the customer relationship. Companies like Amazon, Google, and Apple — with critical distribution and financial services infrastructure — are well-positioned in commerce.

RELATED RESEARCH FROM CB INSIGHTS

• How generative AI could supercharge retailers’ ad networks
• AI is revitalizing the “virtual try-on” space — this is what’s coming next, including interactive Google ads
• The enterprise AI agents & copilots market map
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• Generative AI — e-commerce search
• AI-optimized e-commerce UX
• Generative AI — customer support operations

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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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Open-source AI is drawing unprecedented attention from developers and enterprises, driven in part by DeepSeek’s recent model releases.

Cost pressures and demands to improve the performance of generative AI applications are driving enterprise interest in the ecosystem as organizations seek more flexible and cost-effective alternatives to proprietary solutions. 

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January was a busy month for the generative AI space, headlined by DeepSeek‘s R1 model launch — matching OpenAI’s o1 model capabilities at just 5-10% of the cost, while open-sourcing the technology.

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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

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The AI company, which emerged from Liang Wenfeng’s hedge fund High-Flyer, released an open-source reasoning model (named R1) in January 2025 that rivals the performance of OpenAI’s o1 reasoning model.

DeepSeek says it trained its base model with limited chips and about $5.6M in computing power — a fraction of the $100M+ US rivals have spent training similar models — thanks to some clever techniques.  

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