Big Tech – CB Insights Research https://www.cbinsights.com/research Tue, 19 Aug 2025 17:25:27 +0000 en-US hourly 1 Cloud Wars: How Amazon, Microsoft, and Alphabet are preparing for an AI future https://www.cbinsights.com/research/briefing/webinar-cloud-wars/ Wed, 21 May 2025 19:58:23 +0000 https://www.cbinsights.com/research/?post_type=briefing&p=174012 The post Cloud Wars: How Amazon, Microsoft, and Alphabet are preparing for an AI future appeared first on CB Insights Research.

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]]> Battle of the Cloud Titans: How Amazon, Microsoft, and Alphabet are preparing for an AI future https://www.cbinsights.com/research/report/battle-cloud-titans-alphabet-amazon-microsoft/ Wed, 21 May 2025 16:21:30 +0000 https://www.cbinsights.com/research/?post_type=report&p=173998 The AI boom is creating massive cloud computing needs that the top 3 global cloud providers — Amazon, Microsoft, and Alphabet (Google) — are racing to address and monetize. AI is already fueling revenue growth for these cloud giants.  First, AI workloads …

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]]> The AI boom is creating massive cloud computing needs that the top 3 global cloud providers — Amazon, Microsoft, and Alphabet (Google) — are racing to address and monetize.

AI is already fueling revenue growth for these cloud giants. 

AI sparks cloud growth acceleration: How the cloud giants are seeing rebounding cloud revenue growth thanks to AI

First, AI workloads require more computing resources than traditional workloads, thus increasing per-customer spending. Second, AI companies (with their own computing needs) are proliferating rapidly, now capturing 20% of all venture deals globally. Together, these trends create both enormous revenue opportunities and unprecedented infrastructure challenges.

At the same time, new competitors are emerging to serve this insatiable demand. The OpenAI-led Stargate Project, with its planned $500B investment, threatens to reshuffle the cards in the cloud computing space that AWS has led for over a decade in terms of market share.

In response, cloud providers are spending tens of billions to capture their share of AI computing spend.

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In the 19-page report, we cover 3 strategic pillars that emerged from our analysis:

  • Cloud providers are investing heavily in compute infrastructure to meet explosive AI demand. Amazon, Alphabet, and Microsoft are planning a combined $250B+ in capex spend, primarily for AI data centers, in 2025 in addition to vertically integrating into energy production with 6 nuclear partnerships and creating custom AI chips to control costs and gain competitive advantages.
  • Strategic partnerships and ecosystem development are key to cloud dominance, as providers lock in strategic partnerships with leading model developers (such as Microsoft’s $13B investment in OpenAI), develop proprietary foundation models, and build out accelerator programs to seed AI ecosystems. For example, Amazon expanded its genAI-focused accelerator from 21 to 80 startups between 2023 and 2024 while more than tripling the value of the cloud credits offered.
  • Cloud providers are expanding their AI service portfolios into agentic AI and security to drive adoption and consumption. Alphabet recently made its largest acquisition ever to expand into the cloud security space, spending $32B to buy Wiz, while all 3 players are racing to expand their agentic AI offerings, including developer tools, dedicated marketplaces, and customizable agents.

Additional resources:

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]]> How the rise of humanoid robots launches AI into the physical world https://www.cbinsights.com/research/humanoid-robots-launch-ai-into-physical-world/ Thu, 08 May 2025 18:28:08 +0000 https://www.cbinsights.com/research/?p=173830 The AI landscape is evolving from digital domains to the physical world. After generative AI transformed content creation with large language models and AI agents enabled autonomous decision-making with predictive systems across enterprises and industrial applications, humanoid robots represent the …

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]]> The AI landscape is evolving from digital domains to the physical world.

After generative AI transformed content creation with large language models and AI agents enabled autonomous decision-making with predictive systems across enterprises and industrial applications, humanoid robots represent the next frontier as the embodiment of physical AI.

The humanoid market secured a record $1.2B in funding in 2024 and is projected to reach $2.3B in 2025, according to CB Insights data.

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]]> Building the agent economy: How cloud leaders are shaping AI’s next frontier https://www.cbinsights.com/research/ai-agent-strategy-top-cloud-providers/ Wed, 07 May 2025 20:26:24 +0000 https://www.cbinsights.com/research/?p=173769 As the AI boom accelerates, the top 3 global cloud providers — Amazon, Microsoft, and Google — are racing to capture a larger share of enterprise AI spend. Central to this shift is the rise of AI agents: intelligent systems …

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]]> As the AI boom accelerates, the top 3 global cloud providers — Amazon, Microsoft, and Google — are racing to capture a larger share of enterprise AI spend. Central to this shift is the rise of AI agents: intelligent systems capable of performing multi-step tasks, interacting autonomously with tools and data, and automating business workflows.

Drawing on CB Insights’ Business Graph, which links data across private investments, business relationships, and public company disclosures, we surface key signals on how each cloud player is positioning itself in the agentic AI space and what their next move could be.

While all 3 providers are investing heavily in infrastructure to support agentic AI, they are taking distinct paths to monetization and market control — from proprietary models and low-code build tools to strategic partnerships and go-to-market accelerators.

Understanding these differences will prove critical in evaluating cloud alignment, competitive positioning, and agent-enabled product strategy.

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Key takeaways

  • Amazon positions itself as a neutral infrastructure layer for the agentic ecosystem, betting on in-house chips and seeding its ecosystem with 16 total investments in agent startups. These investments, which primarily take the form of cloud credits rather than equity, form a low-risk, high-volume strategy to lowering the barriers to building on AWS. Amazon’s approach combines enterprise enablement with strategic consumer-facing investments, signaling potential integration with its broader ecosystem.
  • Google’s agentic offering centers around its Gemini foundational models, creating an open marketplace for partner-built agents leveraging its technological leadership — supported by 46 total partnerships and its Agent2Agent protocol. This partner-centric approach means Google can quickly populate its marketplace with specialized agents while maintaining Gemini as the differentiating foundation technology.
  • Microsoft emphasizes a pre-built suite of agentic solutions to drive enterprise adoption, embedding Copilot agents throughout its productivity ecosystem. The company recently achieved 15M GitHub Copilot users, up 4x YoY, and recorded 1M custom agents created on its SharePoint and Copilot Studio platforms. Microsoft’s expansive enterprise client base gives it an in-built audience for new agent products.

Amazon positions itself as the neutral infrastructure layer for the agentic ecosystem

Amazon is approaching the agentic AI landscape as a pragmatic infrastructure provider, with a strategic bias toward enabling partners rather than competing with its own agent suite. This partner-first approach comes at a critical time, as Amazon has been playing catch-up in the agentic race — although recent moves, including forming a dedicated agentic AI group in March 2025 and unveiling its Nova foundational models in December 2024, signal a growing focus.

Amazon is betting on its in-house chips, Trainium and Inferentia2, to attract agentic AI workflows, as these chips can help reduce the cost and energy consumption associated with AI model training and inference. Amazon has already formed several partnerships with agentic AI startups such as Poolside and NinjaTech for them to train and run their AI agents on its in-house chips.

This approach — of providing robust infrastructure and letting specialized partners build solutions on top — is also reflected in its agent development tool offerings. While developers can build agents using Amazon Bedrock Agents, Amazon (unlike Google or Microsoft) doesn’t directly emphasize low-code/no-code solutions, instead enabling partners like SnapLogic to build such tools on its platform. 

The company has also been investing heavily in agentic AI startups, with 16 unique investments since 2023 — more than both Google and Microsoft combined. However, 12 of these were made through non-equity accelerator programs that provide cloud credits and technical enablement rather than capital. 

This low-risk, high-volume approach lowers the barriers to building on AWS while seeding future clients at minimal cost. It also embeds AWS infrastructure into early-stage agent development, capturing mindshare before competitors can gain traction.Amazon’s investments reveal a strategic interest in consumer-facing AI applications that complement its existing business. Three of its four equity investments are in consumer-focused companies — Please and NinjaTech (personal AI agents) and Cartesia (voice AI) — aligning with Amazon’s consumer strategy and the recent launch of Nova Act, its web-browsing agentic AI targeting developers. 

These investments suggest AWS is taking a dual strategy: framing itself as an enterprise infrastructure provider for partners while developing consumer-facing capabilities that could enhance Amazon’s broader ecosystem, including potentially a revamped Alexa.

This could lead Amazon to make an acquisition that accelerates monetization of consumer-facing agents. Acquiring a startup developing agent payment infrastructure, for instance, would support efforts to enable autonomous transactions.

Google’s agentic offering centers around its Gemini foundational models

Google has positioned itself as the central platform provider in the agentic AI landscape, building a comprehensive ecosystem centered around its proprietary Gemini foundation models. Unlike Amazon’s infrastructure-focused approach or Microsoft’s enterprise application strategy, Google is creating an open marketplace for partner-built agents that leverage its technological leadership.

To boost adoption of its Gemini models for agentic AI, Google unveiled its AI Agent Space last year, a dedicated marketplace exclusively for partners’ agents. This is complemented by Google’s agent interoperability initiative, the Agent2Agent (A2A) protocol, which enables AI agents to communicate effectively regardless of their underlying frameworks or vendors. As a sign of traction for A2A, Microsoft recently announced it would adopt the protocol, in addition to the 50+ supporting partners Google already unveiled early April this year.

Google leads in agent-related partnerships with 46 collaborations — 2x as many as Microsoft and Amazon. Almost half of these are with agentic AI startups, including AI coding agents like Cursor, Augment Code, and Replit. This partner-centric approach means Google can quickly populate its marketplace with specialized agents while maintaining Gemini as the differentiating foundation technology.

Source: CB Insights — Google’s business relationships. Note: includes business relationships for Google Cloud.

Enterprise partnerships also demonstrate Google’s strategy in action. Its recent Salesforce collaboration will empower Salesforce customers to build Agentforce agents using Gemini, while Deloitte has launched over 100 ready-to-deploy AI agents powered by Google’s models. According to Google Cloud, more than 60% of generative AI startups are now building on its platform.

Google has also been partnering with leading venture capital firms and accelerators, like Sequoia, Lightspeed, and Y Combinator, to promote the use of its technology (such as TPUs and Gemini models) to fast-growing startups that are building with AI. 

Google’s development toolkits — Vertex AI Agent Builder, Agent Designer in Agentspace, and Agent Development Kit — offer solutions for both technical developers and non-technical users, reflecting Google’s goal of becoming the complete platform for agent creators and consumers alike. 

Rather than building a comprehensive first-party agent suite, Google is embedding itself into the tech stack of emerging agentic players, making Gemini the platform of choice for agent innovation. 

To maintain its edge in safe scaling and cross-agent coordination, Google may look to acquire companies focused on monitoring, governance, and lifecycle tooling, such as Galileo — a leader in AI evaluation backed by Databricks and ServiceNow.

Microsoft emphasizes a pre-built suite of agentic solutions to drive enterprise adoption

Microsoft’s offerings center around a comprehensive suite of pre-built agents deeply integrated into its productivity ecosystem. While Amazon focuses on infrastructure and Google on promoting its foundational models, Microsoft aims to deliver immediate business value through turnkey solutions.

The company leads the market in pre-built agent offerings, with its Copilot suite including Analyst, Researcher, Security, and Dynamics 365 autonomous agents — all powered by its exclusive access to OpenAI’s models. 

This strategy has driven strong adoption: Microsoft’s Q3 FY’25 earnings call revealed that GitHub Copilot’s developer base has surpassed 15M users (up 4x YoY), while 1M custom agents were created during that quarter through Copilot Studio and SharePoint.

Source: CB Insights — Microsoft Earnings Insights

Microsoft’s development tools (Copilot Studio, Azure AI Agent Service) cater to both technical and non-technical users, but the company’s primary advantage comes from embedding agentic capabilities throughout its productivity ecosystem. The November 2024 launch of Magentic-One, a multi-agent system for enterprise deployment, further enhances Microsoft’s position in business workflows.

Unlike Amazon’s broad ecosystem-seeding or Google’s push to embed Gemini models into any agentic workflow, Microsoft concentrates on initiatives that complement its in-house agentic tools. Its partnership with Moveworks exemplifies this strategy, allowing employees to access Moveworks’ specialized agents directly within Microsoft 365 Copilot and Teams.

Microsoft’s approach demonstrates the power of integration over technological differentiation in driving enterprise adoption. By leveraging its existing relationships and software suite, Microsoft has established dominance in high-value business workflows where agentic AI delivers immediate productivity gains — and where competitors must overcome Microsoft’s entrenched position.

To round out its Copilot suite and reinforce its workflow ownership strategy, Microsoft may seek acquisitions in sectors where it lacks native agent offerings, like recruiting, healthcare administration, or logistics.

Related research on AI agents and big tech:

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]]> AI is making big tech even bigger — here’s how the trillion-dollar tech giants are deepening their moat and fueling future growth https://www.cbinsights.com/research/report/big-tech-ai-future-growth-charts/ Fri, 11 Apr 2025 20:53:59 +0000 https://www.cbinsights.com/research/?post_type=report&p=173547 Big tech companies — Alphabet (Google), Amazon, Apple, Meta, Microsoft, and Nvidia — earned nearly $2T in aggregate revenue in 2024, up 15% from 2023.  They already dwarf the private tech sector — surpassing the combined value of all 1,200+ …

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]]> Big tech companies — Alphabet (Google), Amazon, Apple, Meta, Microsoft, and Nvidia — earned nearly $2T in aggregate revenue in 2024, up 15% from 2023. 

They already dwarf the private tech sector — surpassing the combined value of all 1,200+ unicorns by a factor of 3 — and after a period of layoffs, they’re back to hiring, with 2024 headcount growing an average of 7% YoY.

Now, they’re betting big on AI to power their next phase of growth. 

Spending on AI infrastructure (including data centers) has sent their capital expenditures to unprecedented levels. The venture arms of Nvidia, Google, and Amazon all backed a record number of AI deals last year. And after a years-long slump in big tech M&A, AI acquisitions will likely drive a rebound in 2025.

Below, we dive into how AI is reshaping dynamics among big tech players — including deep dives into fast-emerging markets like humanoids and AI agents — across 7 charts.

Note: We include US-based big tech companies based on market cap ($1T+) as of 04/11/2025.

BIG TECH’S AI BETS

Get an Excel file with US tech giants’ AI investments and acquisitions since 2023.

Big tech heads toward $300B+ in 2025 capex

Increased spend on AI infrastructure like high-powered data centers has driven Amazon, Microsoft, Alphabet, and Meta’s combined capex past $50B in recent quarters. 

Meta CEO Mark Zuckerberg framed Meta’s capex spend as a “strategic advantage” on its Q4’24 earnings call as the company scales AI usage across its products. Meta plans to spend $60-65B in capex in 2025.

Stacked bar chart showing "Big tech's AI-fueled spending spree" with combined capital expenditures per quarter for Amazon, Microsoft, Alphabet, and Meta from 2020-2024. The chart shows dramatic growth in spending, reaching approximately $72B in Q4 2024, more than triple the ~$20B quarterly spending in early 2020.

As AI model costs drop, cloud providers in particular expect they will benefit from the expanding market. 

Microsoft CEO Satya Nadella emphasized this potential on the company’s recent earnings call: “We ourselves have been seeing significant efficiency gains in both training and inference…as AI becomes more efficient and accessible, we will see exponentially more demand.”

To capture the demand, the big 3 are planning major infrastructure investments: 

  • Amazon projects $100B in capex in 2025, up from $83B in 2024
  • Microsoft has committed $80B in 2025 to build out AI data centers
  • Google expects $75B in capex in 2025

Cloud competition hinges on AI demand

AI demand is turning into cloud revenue for Amazon, Google, and Microsoft. 

AI sales have helped boost revenue growth for Microsoft’s Azure and cloud services arm, which averaged 31% quarterly growth in 2024, up from 28% in 2023.

Google Cloud’s more muted growth in Q4’24 (down 5 percentage points quarter-over-quarter) sent Alphabet’s shares down in February. Both Microsoft and Alphabet cited compute capacity constraints as reasons for the more limited growth in their latest quarters. 

Bar charts showing year-over-year cloud revenue growth for AWS, Google Cloud, and Azure from 2022-2024. The headline notes "Microsoft attributes 13 points of Azure's growth to demand for AI services in latest quarter." Azure shows 31% growth in Q4 2024, Google Cloud 30%, and AWS 19%.

Expect close investor attention in 2025 to cloud revenue growth, especially as these players accelerate their infrastructure spend. AWS’ $28.8B in Q4’24 revenue was nearly on par with Amazon’s capex spend overall ($27.8B). 

Meanwhile, as cloud competition intensifies, providers are strengthening their security offerings to capture enterprise clients with stringent compliance requirements. 

Google Cloud has made notable investments in cloud security through strategic acquisitions including Wiz, Siemplify, and Mandiant. In contrast, AWS primarily leverages its partner network for security solutions, collaborating with companies like Bitdefender for endpoint security and CrowdStrike for incident response. 

Their divergent approaches represent another dimension where cloud giants are competing for enterprise wallet share, beyond just AI compute capacity.

2025 likely to bring a rebound in M&A

Tech giants have pulled back dramatically on M&A in the last few years amid the antitrust climate. But with a new US administration in office, tech giants are betting on a friendlier dealmaking environment.

Notably, Google parent Alphabet announced a $33B acquisition of cloud security firm Wiz in March — the biggest VC-backed M&A exit ever. It’s also the first billion-dollar big tech acquisition since 2023, when Microsoft’s Activision deal closed. 

In 2024, Nvidia led acquisition activity, with a focus on companies optimizing AI workloads (Run:AI, Deci, Octo AI). It’s already made 2 more acquisitions in 2025 so far: synthetic data generation startup Gretel in March; and server-renting service Lepton AI in April.

BIG TECH’S AI BETS

Get an Excel file with US tech giants’ AI investments and acquisitions since 2023.

While tech giants test the M&A waters, we also expect to see more “quasi-acquisitions” — for instance, hiring away the teams and licensing the tech of promising startups to avoid antitrust scrutiny. For example, Amazon hired robotic startup Covariant’s founders and a quarter of its staff, while licensing the company’s models, in August 2024. 

Bar chart showing the number of publicly disclosed acquisitions by big tech companies (Amazon, Apple, Google, Meta, Microsoft, and Nvidia) from Q1 2020 to Q2 2025 (as of 4/11/25). The chart shows a decline in acquisitions during 2023 (reaching a low of 1 in Q3 2023) followed by a recent uptick in 2024. The chart also highlights top acquisitions since 2024, including Alphabet's acquisition of Wiz for $33B, and Nvidia's acquisitions of Run ($700M), Deci ($300M), and OctoAI ($250M).

Nvidia accelerates AI startup investments

Nvidia has leapfrogged other big tech companies like Microsoft and Amazon in AI dealmaking. 

The chip leader’s AI startup investments nearly 5x’d between 2022 and 2023. Of course, many of its investments — like Perplexity and xAI — are in turn using its chips.  

The upswing indicates the strategic importance it’s placing on being a player in the AI startup landscape. 

Line graph titled "Nvidia's AI startup investments surge" showing the number of AI equity deals backed by big tech from 2020-2024. Nvidia shows dramatic growth of 444% since 2022, reaching 49 deals in 2024, tied with Google at 49 deals, followed by Microsoft (24) and Amazon (20).

Nvidia also takes the lead when it comes to the strength of its AI startup portfolio. According to CB Insights’ Mosaic scores — which measure private-company health and growth potential, on a scale of 0-1,000 — Nvidia’s AI investments since 2024 come out on top with an average score of 840. 

Nvidia is followed by Microsoft, with an average Mosaic score of 750 among its AI investments since 2024.

Horizontal bar chart showing "Nvidia's recent AI investments have the strongest Mosaic scores" comparing average Mosaic scores (CB Insights' metric for company health and growth potential) for AI companies backed since 2024. Nvidia leads with 840, followed by Microsoft (750), Google (717), and Amazon (710).

Physical AI in focus

Big tech is aggressively pursuing the humanoid robotics space. 

In February 2025, for example, Google joined Apptronik’s $403M Series A funding round while Meta formed a new unit under its Reality Labs hardware division to develop humanoids.

Humanoids are complicated to build and deploy, requiring substantial sensor processing, advanced control, and more.

Tech giants see this as an opportunity to flex their software muscle and deep pockets. AI breakthroughs are unlocking new robotic capabilities, allowing humanoids to complete more complex tasks in a shorter training window, with applications from industrials to healthcare. 

Table titled "Big tech lays groundwork for humanoids" summarizing investments and pilots in humanoid robotics. Amazon, Microsoft, Google, and Nvidia are shown to have internal development, investments, and partnerships, while Meta and Apple have only internal efforts. Details include specific partnerships like Amazon with Agility Robotics and SKILD AI, and Nvidia with Figure and Foxconn.

Race to own AI agents

Increasingly capable AI agents will reshape industries as we know them. 

Big tech is getting in on the ground floor — each company is developing agents or building the tooling for them. 

We expect big tech players (alongside LLM developers) to dominate general-purpose agent use cases, such as in commerce, given their distribution and infrastructure edge. Read more in our report on AI agent trends to watch.

Table titled "The AI agent arms race" showing big tech companies' involvement in AI agent development. Microsoft, Google, and Amazon have both development tooling and agent offerings, while Nvidia has only development tooling. Apple and Meta are marked as "working on it/piloting" with agent offerings. The table includes details about each company's specific AI agent products and services.

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]]> Nvidia’s next big bet? Physical AI https://www.cbinsights.com/research/nvidia-next-big-bet-physical-ai/ Wed, 26 Mar 2025 13:59:20 +0000 https://www.cbinsights.com/research/?p=173369 This research comes from the March 25 edition of the CB Insights newsletter. You can see past newsletters and sign up for future ones here. M&A is back. Below, we break down what’s driving the surge in deals, then zoom in on Nvidia’s …

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]]> This research comes from the March 25 edition of the CB Insights newsletter. You can see past newsletters and sign up for future ones here.

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.

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CB Insights chart titled 'Wiz fuels record-breaking M&A activity' showing Q1 2025 set a new all-time high for $B+ startup acquisitions with $54.5B total. The stacked bar chart highlights Wiz's $33.0B acquisition as the largest, followed by Ampere at $6.5B, and other acquisitions including Moveworks ($2.9B), Next ($2.6B), Poppi ($2.0B), and others ranging from $1.0B to $1.7B. Data as of 03/23/2025.

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.

CB Insights bar chart showing tech M&A prices declining 50% since 2020. The chart displays average tech M&A deal valuations dropping from $93M in 2020 to $47M in 2024, with intermediate values of $71M (2021), $76M (2022), and $61M (2023). Source cited as CB Insights M&A transaction data.

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. 

CB Insights quadrant chart titled 'Synthetic training data — tabular & text' showing company positioning based on execution strength (vertical axis) and market strength (horizontal axis). The chart categorizes companies as Leaders, Outperformers, Highfliers, and Challengers. Gretel is highlighted as a Leader with strong positioning, while various other synthetic data companies are positioned throughout the quadrant.

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.

CB Insights earnings call transcript showing Nvidia CFO Colette Kress discussing 'physical AI' as AI's next evolution. The transcript from Q4 FY 2025 shows Kress explaining how Nvidia infrastructure is being adopted for robotics and physical AI, highlighting the Nvidia Cosmos world foundation model platform for revolutionizing robotics, with early adoption by companies including Uber.

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.

Nvidia strategy map showing AI ecosystem partnerships. The map displays Nvidia at the center, with connections to different AI sectors including: Digital Twins (featuring partners like Siemens, Hexagon), Horizontal AI applications, AI agents & copilots (showing Imbue, Kore.ai), Multimedia generation (showing Luma.AI, Runway, Getty Images), and Networking. Also shows Generative AI Foundation Models partners like AI21Labs, Aleph Alpha, Essential AI, Hugging Face, and together.ai.

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]]> Global AI race heats up in India with unprecedented hiring spree https://www.cbinsights.com/research/ai-india-hiring-headcount-growth/ Fri, 21 Mar 2025 19:50:48 +0000 https://www.cbinsights.com/research/?p=173275 Global tech leaders are establishing positions in India’s fast-growing AI sector. 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 …

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]]> Global tech leaders are establishing positions in India’s fast-growing AI sector.

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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]]> Google’s biggest acquisitions https://www.cbinsights.com/research/google-biggest-acquisitions-infographic/ https://www.cbinsights.com/research/google-biggest-acquisitions-infographic/#respond Thu, 20 Mar 2025 15:00:20 +0000 https://www.cbinsights.com/research/?p=20080 Google has disclosed over 270 acquisitions in its history. Its biggest acquisition to date came in March 2025, when it bought cloud security company Wiz for $33B — nearly 3x the value of its $12.5B acquisition of Motorola Mobility in 2012. …

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]]> Google has disclosed over 270 acquisitions in its history.

Its biggest acquisition to date came in March 2025, when it bought cloud security company Wiz for $33B — nearly 3x the value of its $12.5B acquisition of Motorola Mobility in 2012. (It sold Motorola Mobility off after just 2 years for a quarter of the acquisition price.)  

Using CB Insights M&A data, we made a visual timeline of the largest acquisitions in Google’s history. See the list of top 10 below.

Please click to enlarge.

Timeline of Google's biggest acquisitions

KEY TAKEAWAYS

  • Google has spent nearly $65B on its top 10 acquisitions.
  • All 10 of the top deals pictured had valuations greater than $1B, including marketing solutions provider DoubleClick ($3.1B, 2007) and navigation app Waze ($1.15B, 2013). YouTube ($1.7B, 2006) was Google’s first $1B+ acquisition.
  • These top deals reflect Google’s strategy evolution, from adtech (AdMob, DoubleClick) in the late 2000s to mobile (Motorola Mobility) and wearables (Fitbit) in the 2010s to cloud computing and security (Mandiant, Looker, Wiz). 

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]]> https://www.cbinsights.com/research/google-biggest-acquisitions-infographic/feed/ 0 Zuckerberg vs. Altman: A showdown in social AI https://www.cbinsights.com/research/zuckerberg-altman-social-ai/ Wed, 05 Mar 2025 22:04:20 +0000 https://www.cbinsights.com/research/?p=173157 This research comes from the March 4 edition of the CB Insights newsletter. You can see past newsletters and sign up for future ones here.  AI chatbots saw a record 427M app downloads last quarter — up 42% vs. Q3. Now …

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]]> This research comes from the March 4 edition of the CB Insights newsletter. You can see past newsletters and sign up for future ones here. 

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.

Consumers downloaded AI chatbot apps a record 427M times in Q4'24

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.

Sam Altman's post on X: "ok fine maybe we'll do a social app"

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.

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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.

Mercedes-Benz earnings call transcript that speaks to the sociability of its in-vehicle experience

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.

A table depicting big tech's AI agent activity and key developments

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:

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]]> Tech M&A Predictions for 2025 https://www.cbinsights.com/research/briefing/webinar-tech-ma-predictions-2025/ Mon, 24 Feb 2025 21:34:48 +0000 https://www.cbinsights.com/research/?post_type=briefing&p=173064 The post Tech M&A Predictions for 2025 appeared first on CB Insights Research.

]]> The post Tech M&A Predictions for 2025 appeared first on CB Insights Research.

]]> The foundation model divide: Mapping the future of open vs. closed AI development https://www.cbinsights.com/research/report/future-of-foundation-models-open-source-closed-source/ Wed, 08 Jan 2025 20:08:44 +0000 https://www.cbinsights.com/research/?post_type=report&p=172479 This is part 1 of 2 in our series on the generative AI divide. In part 2, we will cover considerations for enterprise adoption of open & closed models.  The divide between open-source and closed-source AI models is reshaping tech …

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]]> This is part 1 of 2 in our series on the generative AI divide. In part 2, we will cover considerations for enterprise adoption of open & closed models. 

The divide between open-source and closed-source AI models is reshaping tech industry dynamics. 

Tech leaders have staked out clear positions: Meta and xAI are open-sourcing models like Llama 3.1 and Grok-1, while Google and OpenAI have largely walled off their systems. Investment flows are also split between both approaches. Since 2020, private open-source AI model developers have attracted $14.9B in venture funding, while closed-source developers have secured $37.5B — reflecting different bets on how AI innovation will unfold.

The core difference lies in access: closed-source approaches keep model details and weights proprietary, while open-source development makes these elements available so models can be more freely studied, run, and adapted.

Open-source vs. closed-source model developers tearsheet

Companies building generative AI applications must understand this evolving landscape as it has crucial implications for the infrastructure they adopt. Based on current trends, we expect:

  1. Consolidation around frontier models: Closed-source models from players like OpenAI, Anthropic, and Google will dominate the market. Only tech giants like Meta, Nvidia, and Alibaba are likely to sustain the costs of developing open-source models that can compete on performance with proprietary ones. Frontier model training costs are growing 2.4x annually, driven by hardware, staffing, and energy needs, according to Epoch AI.
  2. Revenue and investment gaps threaten open-source model developers’ viability: While burning cash, closed-source leaders like Anthropic and OpenAI lead the private market in funding, revenue, and commercial traction. Open-source developers face similar costs but struggle to generate revenue or attract capital investment ($14.9B vs. closed-source’s $37.5B since 2020). This suggests they will move to commercialize their closed models (e.g., Mistral AI) and/or pivot to smaller, specialized offerings (e.g., Aleph Alpha).   
  3. Smaller models drive open-source adoption: Industry leaders, alongside a range of smaller players, are releasing smaller, specialized open-source models, as evidenced by Microsoft‘s Phi, Google’s Gemma, and Apple‘s OpenELM. This suggests a two-tier market for enterprises evaluating the landscape: closed-source frontier models for the most sophisticated applications and open-source smaller models for edge and specialized use cases.

Below, we use CB Insights data to map out the open-source and closed-source AI landscape. Our analysis focuses on foundation models — the powerful, general-purpose AI systems that form a critical infrastructure layer.

CB Insights customers can track every company mentioned in this analysis using this search. We used the Generative AI — large language model (LLM) developers and Generative AI — image generation market profiles to establish the private market landscape, focusing on companies that have received funding and are developing foundation models. 

Get a download of foundation model developers

This Excel file includes funding, valuation data, and more for 30+ companies.

Table of contents

Consolidation around frontier models

  • Industry leaders are divided in their approaches
  • Closed-source developers lead the private market in equity funding
  • Performance gaps converge, with largest companies’ models topping leaderboard

Revenue and investment gaps threaten open-source model developers’ viability

  • OpenAI dominates LLM adoption and revenue, followed by Anthropic
  • Open-source’s path to revenue remains unclear
  • Investors hedge their bets

Smaller models drive open-source adoption

  • A wave of smaller foundation model players will move away from frontier model development
  • Market bifurcation accelerates

Consolidation around frontier models

Industry leaders are divided in their approaches 

Many big tech companies — like Google and Apple — are releasing a combination of open and closed models, typically keeping their flagship models proprietary while releasing lighter-weight open models as an extension of their research efforts.

Meta and Nvidia, meanwhile, are also open-sourcing flagship models. 

Table highlighting how big tech prioritizes closed flagship models while releasing lighter-weight open models

Note: When developers “open-source” AI models, they do so on a spectrum, publicly disclosing some combination or element of the: model weights (the learned parameters of a neural network, crucial for the model’s performance and capabilities as they encapsulate the knowledge acquired during training), underlying source code, and original training data. Open-sourcing may also involve licensing the model for free commercial use.

Open-source proponents are preparing for an open-source future

Meta CEO Mark Zuckerberg wrote in July that “Meta is committed to open source AI,” with the belief that an open ecosystem will eventually become the standard. On earnings calls, Meta is the most active big tech company in terms of open-source mentions. 

At the same time, Zuckerberg acknowledged in April on Dwarkesh Patel’s podcast that the company will only continue open-sourcing “as long as it’s helping us.” 

In July 2024, Meta released the model weights for its latest Llama model family so developers can fine-tune the model (train it on custom data). However, the source code and model architecture remain unavailable, limiting full modification or analysis. Meanwhile, Nvidia released both the model weights and training code for its NVLM 1.0 family of large multimodal language models in September 2024. 

Closed-source proponents view revenue as crucial for top resources and talent

For example, Baidu CEO Robin Li said in an internal memo that open-source models “make little sense.” From a business perspective, he noted, “Being closed source allows us to make money, and only by making money can we attract computational resources and talent.”

Safety remains central to the debate

Critics of open-source AI models fear they will be misused by malicious actors to access harmful information (like how to build a bomb or write code for a cyber attack). They also raise national security concerns, with critics suggesting foreign actors’ ability to use open-source models to advance military applications (like weapons systems and intelligence tech) will undermine strategic advantages held by countries that currently lead in AI development. 

Closed models use techniques like Reinforcement Learning by Human Feedback (RLHF) during fine-tuning to limit the harmful content the model can produce. Open models, meanwhile, are more likely to be deployed without these safeguards. 

On the other hand, open-source AI proponents argue, as highlighted in Mozilla’s Joint Statement on AI Safety and Openness with 1,800+ signatories, that increasing access to foundation models will ultimately make them safer, thanks to increased transparency, scrutiny, and knowledge sharing. 

Closed-source developers lead the private market in equity funding

The private market is also split, with closed developers leading in equity funding. 

While both Mistral AI and xAI are proponents of open-source, both of their flagship models are currently closed. 

The cost to develop frontier models — taking into account hardware, staffing, and energy consumption costs — is growing 2.4x per year. This is driving the fundraising race. 

Chart of leading LLM developers by equity funding

Performance gaps converge, with largest companies’ models topping leaderboard

Leading open-source models, like Meta’s largest Llama model, are making their way onto the MMLU leaderboard — a test that evaluates a language model’s knowledge and reasoning skills. The expanded version, MMLU-Pro, includes more challenging questions to assess advanced reasoning capabilities in AI models.

At the same time, proprietary models continue to outpace open-source ones by several months in terms of release dates. 

Leaderboard highlighting leading foundation models according to MMLU-Pro and MMLU benchmarks

The leaderboard itself is dominated by the largest companies in both big tech and the private market, indicating market consolidation at the frontier level. 

At this stage, a16z partner Marc Andreessen has posited we could be approaching a “race to the bottom” — a future point where there are no moats for foundation models, and open-source performance is on par with closed-source. This has come into focus in recent months as frontier labs like OpenAI and Google have focused on smaller model development and other products (like agents) as performance gains slow and as release dates for the largest models (such as a potential GPT-5) get pushed back.

Below we look at how revenue and adoption gaps in the private market also point to increasing consolidation.

Get a download of foundation model developers

This Excel file includes funding, valuation data, and more for 30+ companies.

Revenue and investment gaps threaten open-source model developers’ viability in the private market

OpenAI dominates LLM adoption and revenue, followed by Anthropic

As LLM developers burn through cash, the focus has shifted to customer adoption — and revenue. 

Based on CB Insights business relationship data, OpenAI is far ahead of its peers in terms of its disclosed partnerships and client relationships. 

This business relationship analysis is limited to publicly disclosed partnership, client, and licensing agreements for pure-play model developers to highlight adoption trends. Relationships are not exhaustive and are directionally representative of trends across model developers’ partner and client relationships.

OpenAI dominates LLM adoption based on disclosed business relationships

In terms of revenue, OpenAI leads, with projections of $3.7B in annual revenues for 2024 and $11.6B for 2025. However, it’s also been burning cash: the company projected midway through the year that it would lose $5B in 2024.

Table highlighting revenues of private foundation model developers, led by OpenAI

Open-source’s path to revenue remains unclear

While revenues for open-source model developers are not publicly available in most cases, reports suggest revenue generation is more limited — especially given the competition from Meta’s Llama.

The embattled Stability AI reportedly generated $8M in 2022 and less than $5M in the first quarter of 2024 (while losing over $30M). In June 2024, it secured an $80M funding deal that included the forgiveness of $100M in debts owed to cloud providers and other suppliers. 

Meanwhile, Mistral AI has an unclear path to revenue, per The Information reporting — it sells access to its API, and under 10% of its users pay for Mistral’s larger commercial models through partners. Most of its smaller, open-source models are free. 

Source: CB Insights — Mistral funding insight

Following the traditional approach to monetizing open-source businesses — building paid support offerings or tools (plugins, security, migration, apps on top) around the open-source core — some model developers are now building more enterprise capabilities into their platforms. 

For example, Databricks offers security and other paid support services around its open-source LLM, DBRX. Similarly, Aleph Alpha launched in August 2024 a “sovereign AI” platform designed to help corporations and governments deploy LLMs (not necessarily its own) with added control and transparency features to serve the European market. 

Investors hedge their bets

Most leading investors in private foundation model developers have backed companies developing both closed and open models.

Corporate investors figure heavily — Nvidia, Alibaba, and Microsoft, for example, have offered computing power and funds for development. These investments are aimed at feeding their core business focuses, such as AI chips and cloud computing. AWS, Azure, and Google Cloud all host both open and closed models.

Table highlighting leading investors in foundation model developers

Venture investors are taking sides:

  • Coatue, the leading VC by unique companies backed, has called open source “the heartbeat of AI.” It’s taking a complementary approach: “We see open-source models as firmly having a place alongside proprietary ones.”
  • a16z’s founders are proponents of open-source models, arguing that their transparency and accessibility will help ensure that AI is developed securely and ethically. In 2024, the two largest a16z-backed AI deals went to open-source LLM developers xAI and Mistral AI.
  • Meanwhile, Founders Fund partner John Luttig has argued that the future of foundation models is closed-source. Khosla Ventures’ Vinod Khosla (a backer of OpenAI) also argues in favor of closed-source AI for safety reasons. 

The investor split reflects uncertainty over which ecosystem will dominate and where the greatest value creation will occur. The relative difference in funding totals ($14.9B in equity funding to open-source model developers vs. $37.5B to closed-source), as well as the data available on revenue, suggests that a closed approach for private developers appears poised to win out, especially given the most performant open models at this point are from big tech leaders.

Smaller models drive open-source adoption

A wave of smaller foundation model players will move away from frontier model development 

The conditions of a) high compute costs, b) limited moats, and c) competition from big tech have created a market ripe for a shake-up.

We’re seeing a wave of smaller foundation model players:

  • Collapse into big tech: Adept, Inflection, and Character.AI have all essentially been “acqui-hired” by big tech companies, with founders and large portions of teams joining the acquirers. These deals reflect the high costs of model development, with licensing payments often directed to investors. 
  • Paywall frontier models: Some open-source AI developers now sell access to premium models while keeping basic versions free — similar to strategies used by big tech. For example, Mistral AI’s flagship model Mistral Large is built for commercial use (not open-source) and is available on Azure in partnership with Microsoft.
  • Focus on smaller, open-source models: Developers like Germany-based Aleph Alpha and Israel-based AI21 Labs have shifted in 2024 from competing on general-purpose LLMs to building lighter-weight, optimized models and related AI tools. These models are open-source, with paid services layered on top.

Market bifurcation accelerates

Based on these trends, the AI model market is splitting into two tiers:

  • Frontier models are largely dominated by closed-source offerings from well-funded players (OpenAI, Anthropic, Google), which can sustain growing compute costs. Meta’s Llama remains the most notable open-source alternative.
  • Smaller models, optimized for specific use cases or edge deployment, are supported by a growing open-source ecosystem. These small language models (SLMs) have fewer parameters than LLMs, making them cheaper to train and easier to run.

Industry leaders are releasing smaller, open-source models to advance research efforts and to promote edge applications: Google with Gemma, Microsoft with Phi, and Apple with OpenELM. 

For example, Microsoft highlighted in a recent earnings call: 

“We have also built the world’s most popular SLMs, which offer performance comparable to larger models but are small enough to run on a laptop or mobile device. Anker, Ashley, AT&T, EY, and Thomson Reuters, for example, are all already exploring how to use our SLM Phi for their applications.” — Satya Nadella, CEO of Microsoft, Q2’24 Earnings Call  

Meanwhile, of the 11 private SLM development platforms we identified, roughly half are already in the process of deploying their products.

Smaller, open models are also gaining traction in sectors like financial services and healthcare, where keeping sensitive data on-premises can be a need.

For example, a VP of machine learning at a health insurance company needed a solution for training healthcare models and looked to Hugging Face’s open-source library. In our May 2024 conversation, the buyer highlighted the opportunity of SLMs for their use case:

“I really think small language models are the future. You don’t need these huge proprietary LLMs for the vast, vast majority of use cases that you’re dealing with, especially some of the administrative burden in healthcare that we deal with.”

VP of Machine Learning,
Publicly traded multinational health insurance company

 

For now, it’s clear a hybrid approach is winning with enterprises: they will look to closed-source frontier models for the most sophisticated applications and open-source smaller models for edge and specialized use cases.

 

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]]> Big Tech in Fintech https://www.cbinsights.com/research/briefing/webinar-big-tech-in-fintech-2024/ Thu, 19 Sep 2024 12:07:55 +0000 https://www.cbinsights.com/research/?post_type=briefing&p=170475 The post Big Tech in Fintech appeared first on CB Insights Research.

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]]> Big Tech in Energy: How Amazon, Google, Microsoft, & Nvidia are advancing the global energy transition https://www.cbinsights.com/research/report/big-tech-energy-amazon-google-microsoft-nvidia/ Wed, 04 Sep 2024 16:53:08 +0000 https://www.cbinsights.com/research/?post_type=report&p=170867 The energy sector presents big tech companies with opportunities to address the growing demand for clean energy solutions and meet their sustainability goals. These tech leaders are collaborating with energy incumbents and startups alike to tap into renewable energy sources …

The post Big Tech in Energy: How Amazon, Google, Microsoft, & Nvidia are advancing the global energy transition appeared first on CB Insights Research.

]]> The energy sector presents big tech companies with opportunities to address the growing demand for clean energy solutions and meet their sustainability goals.

These tech leaders are collaborating with energy incumbents and startups alike to tap into renewable energy sources and decarbonize their operations.

While these big tech players are competing in the energy space, they are also developing unique strategies:

  • Amazon is working to decarbonize its transportation and fulfillment center operations, with a focus on hydrogen tech.
  • Google is pioneering new models for clean energy procurement as it works to boost the sustainability of its data center network.
  • Microsoft is focusing on renewable energy sources — like solar and fusion — and carbon capture technologies to meet the growing energy demands of its AI-driven operations.
  • Nvidia is enhancing data center energy efficiency and investing in the development of a green and reliable power grid.

DOWNLOAD THE BIG TECH IN ENERGY 2024 REPORT

Find out where Amazon, Google, Microsoft, and Nvidia are focused in energy — and where they plan to move next.

This report uses CB Insights datasets like investments, acquisitions, business relationships, company scouting reports, earnings transcripts, and more. Learn more about our data here.

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]]> This month in genAI: Moonshot raises $300M, Amazon acquires Perceive, Google launches Gemini Live https://www.cbinsights.com/research/this-month-in-genai-august-2024/ Fri, 30 Aug 2024 19:51:31 +0000 https://www.cbinsights.com/research/?p=170817 The content below was curated by our experts using CBI Instant Insights, a one-click AI analysis and summarization tool. Click on company profiles for more details and sourcing information. NOTABLE DEALS Moonshot | $300M Series B-II at $3.3B valuation Moonshot …

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]]>

The content below was curated by our experts using CBI Instant Insights, a one-click AI analysis and summarization tool. Click on company profiles for more details and sourcing information.

NOTABLE DEALS

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]]> Analyzing Apple’s AI strategy: Small models, spatial computing, and consumer-friendly AI agents https://www.cbinsights.com/research/apple-ai-strategy-partnerships-acquisitions/ Fri, 30 Aug 2024 17:11:14 +0000 https://www.cbinsights.com/research/?p=170756 Apple’s recent moves are a testament to its singular approach to AI development. Unlike big tech peers like Google and Meta, it’s largely kept its in-house model development activity out of the public eye. With a focus on the on-device …

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]]> Apple’s recent moves are a testament to its singular approach to AI development.

Unlike big tech peers like Google and Meta, it’s largely kept its in-house model development activity out of the public eye. With a focus on the on-device user experience — and smaller models as a result — Apple is relying on external large language models (LLMs) from partners like OpenAI to round out its generative AI suite.

Using CB Insights data, we uncovered the 3 biggest strategic priorities in Apple’s AI strategy:

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]]> Big Tech in Healthcare https://www.cbinsights.com/research/briefing/webinar-big-tech-healthcare-2024/ Thu, 22 Aug 2024 14:00:48 +0000 https://www.cbinsights.com/research/?post_type=briefing&p=170078 The post Big Tech in Healthcare appeared first on CB Insights Research.

]]> The post Big Tech in Healthcare appeared first on CB Insights Research.

]]> Big Tech in Fintech: How Amazon and Google are battling to own transactions https://www.cbinsights.com/research/report/big-tech-fintech-amazon-google/ Thu, 08 Aug 2024 20:35:09 +0000 https://www.cbinsights.com/research/?post_type=report&p=170246 Big tech won’t be your next bank — but they’ll play a part in many of your transactions. After nearly a decade of big tech companies venturing into launching their own financial products, the major players have now pulled back. …

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]]> Big tech won’t be your next bank — but they’ll play a part in many of your transactions.

After nearly a decade of big tech companies venturing into launching their own financial products, the major players have now pulled back. Most have shifted to roles as tech providers, broadly supporting advances in financial infrastructure.

Amazon and Google stand out in this area:

  • Amazon is embedding itself in more financial transactions via partnerships, investments, and acquisitions. It’s using these relationships to reach customers across more geographies and a wider range of services. 
  • Google has shifted away from providing financial services and instead is connecting its existing platforms to others’ financial offerings. The company is also investing and partnering to enable digital-first financial tools.

We mined CB Insights data on Amazon’s and Google’s investments, acquisitions, and partnerships, as well as patents and earnings transcripts, from January 2021 to July 2024 to explore how the companies are reengineering their fintech strategies.

Download the full report to see where they are making moves.

BIG TECH IN FINTECH

See where Amazon and Google are making moves in financial services — and where they’ll go next.

This report uses CB Insights datasets like investments, acquisitions, business relationships, earnings call insights, patents, and more. Learn more about our data here.

Big Tech in Fintech

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]]> Big Tech in Healthcare: How Amazon, Google, Microsoft, & Nvidia are looking to transform drug R&D, primary care, and more https://www.cbinsights.com/research/report/big-tech-healthcare-amazon-google-microsoft-nvidia/ Wed, 12 Jun 2024 18:49:45 +0000 https://www.cbinsights.com/research/?post_type=report&p=169238 The $11T+ healthcare industry presents a host of opportunities and challenges for big tech players, from the chance to capture an abundance of consumer data to the pressure to address digitization and connectivity. These leaders are harnessing their existing offerings …

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]]> The $11T+ healthcare industry presents a host of opportunities and challenges for big tech players, from the chance to capture an abundance of consumer data to the pressure to address digitization and connectivity.

These leaders are harnessing their existing offerings — in areas like cloud computing, AI, and hardware — to service healthcare providers and pharmaceutical companies.

While big tech players are competing with each other in this landscape, they are also carving out distinct strategies: 

  • Amazon is going deeper into primary and specialized care.
  • Google is amassing troves of health data, which could play a role in its biotech bets. 
  • Microsoft is equipping healthcare organizations with AI tools to improve clinical research, drug R&D, and care delivery.
  • Nvidia’s long-standing hardware dominance positions it to play a major role in the future of smart hospitals. 

This report uses CB Insights datasets like investments, acquisitions, business relationships, patents, buyer interviews, company scouting reports, and more. Learn more about our data here.

CB Insights Big Tech in Healthcare: June 2024

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]]> Analyzing Google’s healthcare growth strategy: Can the tech giant become the sector’s go-to AI provider? https://www.cbinsights.com/research/google-healthcare-strategy-map-investments-partnerships-acquisitions/ Thu, 25 Apr 2024 21:39:07 +0000 https://www.cbinsights.com/research/?p=167342 Google has recently sharpened its focus in healthcare, where it’s looking to deploy AI throughout the fragmented ecosystem. It’s tackling the issue on all fronts, from investing in AI-enabled care models via Google Ventures, to forging partnerships through its Google …

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]]> Google has recently sharpened its focus in healthcare, where it’s looking to deploy AI throughout the fragmented ecosystem.

It’s tackling the issue on all fronts, from investing in AI-enabled care models via Google Ventures, to forging partnerships through its Google Cloud division, to launching new products that tailor generative AI to healthcare use cases.

These moves seek not only to address the challenges facing the sector, but also to strategically differentiate Google from big tech peers like Nvidia, Microsoft, and Amazon — all of whom are making concerted efforts to integrate AI into healthcare.

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]]> Analyzing Microsoft’s healthcare growth strategy: How the software giant is betting generative AI will transform the sector https://www.cbinsights.com/research/microsoft-healthcare-strategy-map-investments-partnerships-acquisitions/ Fri, 19 Apr 2024 15:57:51 +0000 https://www.cbinsights.com/research/?p=167993 Microsoft is building on its momentum in generative AI to move deeper into healthcare. The tech giant found a major entry point into healthcare workflows when it acquired Nuance for $19.7B in 2022. It followed up on this by expanding …

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]]> Microsoft is building on its momentum in generative AI to move deeper into healthcare.

The tech giant found a major entry point into healthcare workflows when it acquired Nuance for $19.7B in 2022. It followed up on this by expanding its existing relationship with leading EHR vendor Epic to introduce generative AI across clinical workflows, with the aim of improving provider efficiency and mitigating staffing shortages.

Microsoft’s recent relationships also point to an increasing focus on developing and deploying generative AI in the pharmaceutical industry. The tech behemoth is partnering with and investing in startups in drug development, where early applications of generative AI have seen especially strong investor and commercial traction.

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]]> The big tech AI arms race: 75+ AI startups backed by Amazon, Google, Microsoft, and Nvidia https://www.cbinsights.com/research/report/big-tech-ai-investments/ Tue, 12 Mar 2024 16:47:53 +0000 https://www.cbinsights.com/research/?post_type=report&p=167897 Big tech companies — Alphabet (Google), Amazon, Apple, Meta, Microsoft, and Nvidia — are betting big on AI.  Microsoft’s market cap is hovering at all-time highs as investors have gotten behind its embrace of the technology. Meanwhile, Nvidia joined the …

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]]> Big tech companies — Alphabet (Google), Amazon, Apple, Meta, Microsoft, and Nvidia — are betting big on AI. 

Microsoft’s market cap is hovering at all-time highs as investors have gotten behind its embrace of the technology. Meanwhile, Nvidia joined the club after cruising past the $1T and $2T market cap benchmarks in less than a year on the back of demand for its high-end AI chips. 

Where big tech is putting its money — including investments and acquisitions — provides a window into each player’s strategy. The number of AI deals backed by the group increased 57% in 2023 compared to 2022. Notably, Meta and Apple didn’t invest in any AI startups in 2023, though Meta has been active in developing its own open-source AI models and Apple acquired an AI video compression startup last year.

GET THE DATA BEHIND BIG TECH’S AI INVESTMENTS

The full data file contains every big tech AI investment in 2023, including targets’ country, total funding, category, and more.

Below, we map out every AI company backed by big tech and their strategic venture arms in 2023 with key takeaways below.

CB Insights customers can use this search to stay updated on every big tech AI investment, including 2024 deals. 

Big tech's AI investments in 2023 mapped according to category

Key takeaways

1) Big tech continues to pile in on AI infrastructure, nabbing stakes in the next generation of AI startups.

As companies rush to harness AI’s potential, big tech wants to put itself right at the heart of AI value chains.

Some of the largest AI rounds backed by the group in 2023 went to leading foundation models and other development platforms: OpenAI ($10B corporate minority from Microsoft), Anthropic ($2.6B in funding over multiple rounds backed by Google and Amazon), and Databricks ($500M Series I backed by Nvidia’s NVentures with follow-on participation from AWS and Microsoft). 

2) Rivalries in cloud computing drive activity, while some startups bring in multiple big tech backers to remain neutral.

Due to the capital-intensive nature of AI development, startups are linking up with big tech companies like Google, Microsoft, Amazon, and Nvidia to access their cloud infrastructure, chips, and dollars.

In turn, big tech companies are fueling their rival cloud computing and chip businesses.

3) Healthcare and industrials lead big tech’s vertical AI investments.

Nvidia backed 8 AI startups in healthcare & life sciences in 2023, with 7 of these focusing on AI drug discovery, as the chipmaker doubles down on the sector.

Applications in materials development, manufacturing, and warehousing are also drawing the attention of big tech as the sector races to automate operations.

For example, the Amazon Industrial Innovation Fund invested in AI-powered robotics safety startup Veo Robotics in April 2023. Meanwhile, just last month, Microsoft’s M12 and NVentures backed humanoid robotics startup Figure’s $675M Series B. 

4) An emerging focus area is AI companions and agents.

Companies in this category like Inflection are working to make interacting with computers as conversational as it is to talk to people.

A number of companies backed by big tech in 2023, like Adept and Imbue, are building “autonomous agents” — LLM-powered bots that can independently reason and execute tasks.

In this vein, in January 2024, the Amazon Alexa Fund backed a round to AI agent startup MultiOn.

5) Nvidia bursts onto the scene.

Overall, Nvidia has ramped up its activity more significantly — from backing 5 AI startups in 2022 to 32 in 2023 — than any other tech giant as it embeds itself deeper in the generative AI ecosystem.

Apple and Meta, which historically have made fewer investments compared with other giants and do not have venture arms, did not publicly disclose any AI startup investments in 2023. 

Looking ahead

Large acquisitions have been key for big tech to bring in new revenue sources as well as launch new product lines.

But with regulatory pressure hobbling big tech’s acquisition activity, expect these players to lean more heavily on AI partnerships and investments, as well as product launches, in the coming months. 

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]]> AI-powered humanoid robots are coming and big tech wants in https://www.cbinsights.com/research/big-tech-humanoid-robotics/ Fri, 23 Feb 2024 14:00:49 +0000 https://www.cbinsights.com/research/?p=166680 Humanoid robots are gaining momentum as companies across industries race to automate operations for a competitive edge.  These robots resemble the human form and are designed to be multi-talented, making it possible to swap them in for complex tasks normally …

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]]> Humanoid robots are gaining momentum as companies across industries race to automate operations for a competitive edge. 

These robots resemble the human form and are designed to be multi-talented, making it possible to swap them in for complex tasks normally handled by flesh-and-bone employees. Popular robot forms like automated guided vehicles (AGVs) & autonomous mobile robots (AMRs) and collaborative robotic arms are much less flexible.

However, humanoid robots are complicated to build and deploy. They require substantial sensor processing, advanced control, and complex skill execution. They also need multimodal artificial intelligence (AI) to understand the environment around them.

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]]> The Future of Big Tech in AI https://www.cbinsights.com/research/briefing/webinar-future-of-big-tech/ Fri, 26 Jan 2024 21:27:44 +0000 https://www.cbinsights.com/research/?post_type=briefing&p=166755 The post The Future of Big Tech in AI appeared first on CB Insights Research.

]]> The post The Future of Big Tech in AI appeared first on CB Insights Research.

]]> Inside the Google Mafia: The most prolific ex-Google founders https://www.cbinsights.com/research/google-mafia-top-founders/ Tue, 19 Dec 2023 21:42:26 +0000 https://www.cbinsights.com/research/?p=164529 Former Google employees — its alumni network, or “mafia” — have founded 1,200+ companies across a wide range of industries over the past 5 years. These businesses, the majority of which have been backed by VCs like a16z and Sequoia …

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]]> Former Google employees — its alumni network, or “mafia” — have founded 1,200+ companies across a wide range of industries over the past 5 years.

These businesses, the majority of which have been backed by VCs like a16z and Sequoia Capital, have collectively raised $20B+ in equity funding.

Many members of the Google Mafia have founded just 1 business in their post-Google era. However, others have launched multiple, with the most prolific establishing 6 or more.

We analyzed CB Insights Key People data to identify the ex-Googlers who founded the most businesses after leaving the tech giant.

Ricky Jacob

Ricky Jacob was a team lead at Google, focusing on geo content operations for 2 years.

After leaving Google, Jacob launched location-based service provider GeoSpice (products included runner tracking platform Odikyo and event tech developer Eventsito). He also established CommonTrip, which functioned as a sustainability-focused ridesharing platform.

Jacob pivoted to fintech when he established open banking platform Kred (formerly Huepay), banking API platform Paysack, and robo-investing platform TRDR. 

Most recently, the ex-Googler founded Certify Social, a platform that enables organizations to issue non-fungible token (NFT) rewards.

Robert Spiro

Robert Spiro co-founded social search engine Aardvark, which was acquired by Google in 2010. Following the acquisition, Spiro started as a product manager for Google’s social network: Google+.

After departing, Spiro’s founder journey picked up again with Good Eggs, an ethical food delivery startup where he also served as CEO for 4 years.

Following his time at Good Eggs, Spiro maintained a strong focus on the broader impact of his endeavors. For example, in 2017, he co-founded Imagination Machine, which helps create and support companies that have a positive social or environmental impact. That same year, he launched JHO, which serves as a subscription platform for women’s hygiene products.

In the years that followed, he co-founded educational magazine publisher and eco-friendly toy maker Les Mini Mondes and home solar kit provider Beem Energy. In the enterprise tech space, Spiro co-founded a professional training and coaching platform known as UpTogether.

Most recently, he helped create corporate social responsibility startup Good Steps. 

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]]> The future of big tech in 10 charts https://www.cbinsights.com/research/report/big-tech-future-charts/ Wed, 06 Dec 2023 19:20:57 +0000 https://www.cbinsights.com/research/?post_type=report&p=165339 Big tech companies — Alphabet (Google), Amazon, Apple, Meta, Microsoft, and Nvidia — are on track to earn more than $1.65T in aggregate revenue this year. The group has already notched over $200B in profits in 2023.  Nvidia’s entrance into the …

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]]> Big tech companies — Alphabet (Google), Amazon, Apple, Meta, Microsoft, and Nvidia — are on track to earn more than $1.65T in aggregate revenue this year. The group has already notched over $200B in profits in 2023. 

Nvidia’s entrance into the “big tech” ranks comes on the back of the AI revolution: the AI chipmaker saw its revenue soar 206% year-over-year (YoY) in its fiscal quarter ended October 29. 

However, for big tech companies to continue their frenetic pace of growth, they must add billions to their balance sheets each quarter. 

Heightened competition across these companies’ core business lines (cloud computing, advertising, etc.), plus the generative AI shift, is putting pressure on big tech to cut costs and tap into new markets. 

We dive in below across 10 charts. 

Get the big tech investment data book

See each big tech players’ investments and acquisitions going back to 2015.

Big tech’s dominance

Big tech’s prominence in the tech sector is evident in its sheer size compared to the most valuable tech startups. 

The 6 tech giants hold an aggregate valuation of over $11T — nearly 3 times that of the entire billion-dollar unicorn club.

Even the largest unicorns are unlikely to be big tech contenders any time soon. 

Big tech's combined market cap is nearly 3x the aggregate valuation of global unicorns

The club GAINS A NEW MEMBER

Nvidia’s dominance as an AI chipmaker has lifted it into the big tech ranks. The company hit a $1T market cap in Q2’23.

Its rise signals the next platform shift as companies rush to harness AI’s potential.  

Comparison of trillion-dollar big tech companies' current and all-time high market caps

Revenue growth slows

Over the years, big tech has grown revenue at an astounding rate.

But broadly, these companies’ growth is slowing as they get bigger. 

To fuel growth moving forward, they’ll be looking to reach into new markets, while staying at the cutting edge of emerging technologies like generative AI, quantum, and AR/VR. 

Big tech revenue growth slows, with just Nvidia nearly matching 2021 growth rate this year

A return to efficiency

Even big tech players over-expanded in 2021 and have subsequently moved to cut costs.

Though they still employ far more people now than they did in 2020, the pace of hiring will likely remain slower, with a focus on keeping expenses in check.

Employee headcount and layoff count for Google, Amazon, Meta, and Microsoft

Blockbuster acquisitions

Large acquisitions have historically been key for big tech to bring in new revenue sources as well as launch new product lines.

WhatsApp, acquired by Facebook in 2014, now has more than 2B users globally and is among Meta’s fastest-growing services in the US.

Get the big tech investment data book

See each big tech players’ investments and acquisitions going back to 2015.

But regulatory pressure has put a damper on this activity, as we highlight below. 

Microsoft’s $69B acquisition of Activision, which finalized in October 2023, is a recent notable exception. It will bring $7.5B of revenue to Microsoft’s top line.

Every $1B+ acquisition by big tech since 2000 by valuation

Regulatory pressure puts damper on M&A

Big tech M&A volume flatlined in Q3’23.

Though tech giants haven’t gone completely quiet — Microsoft’s Activision deal closed in Q4 after a nearly 2-year fight with regulators — a healthy tech ecosystem requires that they get back in the game. This is likely challenging with the FTC’s current posture. 

In the meantime, expect smaller deals from these players going after key tech capabilities or talent. 

For example, in Q4’22, Apple CEO Tim Cook said, “We’re constantly looking in the market and…[at] which things would provide either intellectual property or talent or preferably both that we would need. And so we’re constantly looking at acquisitions of all sizes.”

Big tech M&A falls to zero in Q3'23

BIG TECH R&D spending FAR EXCEEDS US VC

In the US, big tech companies’ R&D investment outpaces that of overall US venture funding by a wide margin. This underscores the scale these companies play in driving tech innovation. 

Big tech R&D spending reached $174B in the first three quarters of 2023

All in on AI

Tech giants are throwing their weight behind promising AI startups, offering computing power and funds for development, especially in the realm of generative AI.

These investments in turn could feed into their core business focuses, such as cloud computing (Google, Amazon, Microsoft) and AI chips (Nvidia).​

Generative AI is the new battleground: Big tech's overlapping investments in the space

Converging on each other’S territory

Big tech’s revenue sources are increasingly overlapping.

Cloud computing revenue growth, for example, has slowed amid heightened competition and as enterprise customers optimize their workloads. 

Instead, Amazon, Microsoft, and Google are looking to compute-hungry AI to fuel their cloud computing businesses. Microsoft attributed 3 percentage points of Azure’s growth in the most recent quarter to AI.

Comparison of cloud revenue growth for AWS, Google Cloud, and Azure since 2021

Meanwhile, Amazon is continuing to gain share from leaders Google and Meta in the digital advertising realm. 

Comparison of advertising revenue for Amazon, Google, and Meta, 2020 – 2023

As big tech advances on each other’s core businesses, players are also looking for growth in new markets.

Tech giants are bringing disruption to healthcare, fintech, telecom, and other verticals — but not without hiccups. 

Dive in further with all our big tech research here.

Get the big tech investment data book

See each big tech players’ investments and acquisitions going back to 2015.

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