AI is already fueling revenue growth for these cloud giants. 

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.

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:

• Building the agent economy: How cloud leaders are shaping AI’s next frontier
• The AI data center value chain: 12 high-momentum technologies powering the future of AI
• AI is making big tech even bigger — here’s how the trillion-dollar tech giants are deepening their moat and fueling future growth
• Data centers are reshaping nuclear development, driving billions in new power infrastructure investment

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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.

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.

See 4 agent payment infrastructure startups Amazon could acquire

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.

See 20+ AI observability & evaluation startups Google could acquire

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.

Identify which vertical AI agent startups Microsoft could acquire

Related research on AI agents and big tech:

• Enterprise AI agents & copilots: Our growth projections for the $5B+ market
• The AI agent market map
• AI is making big tech even bigger — here’s how the trillion-dollar tech giants are deepening their moat and fueling future growth

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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 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.

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. 

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.

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. 

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. 

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.

See every big tech-backed, private AI company ranked by Mosaic

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. 

CBI customers: Map the industrial humanoid robotics market

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.

RELATED RESEARCH FROM CB INSIGHTS

• The AI agent market map
• The future of the customer journey: AI agents take control of the buying process
• Big Tech in Energy: How Amazon, Google, Microsoft, & Nvidia are advancing the global energy transition
• The foundation model divide: Mapping the future of open vs. closed AI development

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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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This spending is creating opportunities for growth across the AI data center value chain.

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Nvidia has used its experience developing graphics processing units (GPUs) — which were originally developed for applications like gaming but turned out to be rather good at AI tasks — to become a dominant force in AI infrastructure and applications. 

But a host of established companies and startups are investing heavily to capture a share of the growing AI computing market. This includes building new types of chips specifically for training and running AI models, evolving traditional processors like CPUs and GPUs to better support AI workloads, and exploring novel information processing technologies such as quantum and neuromorphic computing. 

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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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While Nvidia initially developed its graphics processing units (GPUs) for gaming, these chips turned out to be ideal for powering AI tasks. Now, the company is focusing its efforts on providing the computing hardware — notably its A100 and H100 GPUs — and the software infrastructure required for developing generative AI applications.

Amid the generative AI rush, Nvidia has grown rapidly. In fact, it recently surpassed Microsoft and Apple to become the world’s most valuable company. To bolster its leadership position and keep ahead of AI computing competitors like AMD and Intel, Nvidia has forged relationships with companies across the AI landscape.

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The company has faced multiple high-profile incidents over the past 6 years — including crashes involving its planes and a fuselage blowout. This series of events has resulted in a decline in consumer trust, aggravated airlines, and lost sales to rival Airbus.

Amid these challenges, Boeing has shaken up its corporate leadership and moved to improve its manufacturing quality. For instance, the company is exploring a reintegration with Spirit AeroSystems to help address production flaws.

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The UK-based company — a licensor of chip designs to industry leaders like Apple, Google, NVIDIA, and Samsung — dominates smartphone chip architecture with a 99% market share.

However, recent years have been marked by uncertainty for the company, with a $40B acquisition by NVIDIA collapsing in early 2022. The deal faced opposition from customers like Qualcomm and Microsoft, as well as intense regulatory scrutiny.

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But fortunes began to improve dramatically in 2014 with the arrival of CEO Lisa Su, who has helped channel the company’s efforts toward high-growth areas like AI. Its stock price has since climbed 25x.

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Wiz landed a $10B valuation in February just 3 years after its founding. Orca was last valued at $1.8B in 2021. 

Both are part of a group of cybersecurity startups — like Aqua Security and Lacework — that have grown rapidly with the cloud computing wave. 

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Private players like Wiz (founded in 2020) and Orca Security (founded in 2018) have ridden this wave to notch $10B and $1.8B valuations, respectively. 

Meanwhile, cybersecurity behemoth Palo Alto Networks ($64B market cap) has acquired more than 10 companies as it built its Prisma Cloud platform and other security offerings. 

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These factors, along with more distributed and remote workforces, are driving the increased need for cybersecurity solutions to protect critical data and operations in cloud environments.

In the market map below, we identify 103 cybersecurity vendors addressing critical aspects of cloud security across 14 different categories. Some larger players are operating in multiple markets and offer bundled services.

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After bringing on a new CEO in 2020 and reprioritizing its investment strategy, the company has aggressively pursued plans to build an ecosystem for automated, connected, and electric vehicles. It has maintained a dual focus on passenger and commercial markets.

At the same time, the company has experienced considerable growth. Its stock price has more than doubled over the past 3 years — and it has also watched its market cap pass that of one of its largest domestic competitors, General Motors. 

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Reflecting this trend, companies in the cloud GPU market are gaining traction as enterprises look to leverage high-performance GPUs without the need for making big investments in on-premises infrastructure. 

For example, cloud GPU startup CoreWeave recently became a vendor for Microsoft to provide additional capacity for running AI applications on its Azure cloud computing platform (which includes ChatGPT-maker OpenAI as a customer).

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The cloud cost optimization market has seen 7 acquisitions since the beginning of 2020 as consolidation gathered pace. We use CB Insights data to analyze the M&A trends in space and how Apptio’s deal compares to others by looking at:

• Cloud cost optimization funding
  
• Apptio’s valuation & acquisitions
• Revenue multiples

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It just announced plans to invest $100M to help companies make use of genAI and also recently launched a 10-week accelerator program focused on supporting generative AI startups. 

The startups selected for its first cohort are aiming to solve challenges like healthcare burnout, illiteracy, and streamlining tedious employee tasks. Participating startups receive $300K in AWS credit to help develop and run their genAI models.

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This achievement is partly attributed to its pioneering work in accelerated computing, which uses specialty hardware to complete demanding software tasks much faster than previously possible.

Initially, this effort was primarily focused on gaming — but NVIDIA’s development of parallel processing in 2006 paved the way for new capabilities in scientific and research applications. This breakthrough allowed multiple computations at a given time instead of sequentially, resulting in much faster processing speeds.

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We mined Yardstiq’s interviews with software buyers as well as vendors’ submitted Analyst Briefings and used these proprietary insights to map the cloud security landscape and help you quickly build your RFP vendor shortlist.

The Cloud Security RFP Vendor Shortlist features RFP insights on 11 vendors including:

• • Aqua Security 
  • Check Point
  • Lacework
  • Netskope 
  • Orca Security
  • Prisma Cloud (by Palo Alto Networks)
  • Wiz
  • And 4 others

Dig deeper into these players with our Cloud Security Vendor Scorecard.

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Download the buyer’s guide to see our overview of this software category and the questions you should be asking, from pricing to integration.

Buyers interviewed for this report include: 

• VP of Information Security, Fortune 500 corporation
• Former CISO, media group with $1B+ market cap
• Principal VP and CTO, Big Four subsidiary
• CISO, $1B+ valuation fintech

Get access to thousands of detailed, analyst-led interview transcripts with Yardstiq, powered by CB Insights. Reserve your Yardstiq subscription here. 

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Download our scorecard to quickly compare the following vendors. To read the interview transcripts for each solution, reserve your Yardstiq subscription here.

• Aqua Security 
• Lacework
• Netskope 
• Orca Security
• Sysdig
• Prisma (by Palo Alto Networks)

Other cloud security vendors mentioned by buyers of these solutions include:

• Rapid7
• Check Point
• Wiz
• Forcepoint
• Qualys

For more firsthand insights from the world’s largest network of software buyers, reserve your Yardstiq subscription here. 

Yardstiq is powered by CB Insights.

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