How NVIDIA, Microsoft, and Google Work Together in AI Infrastructure And How It Locks In Massive Future Revenue
When people look at tech giants, they often imagine a battlefield companies fighting to the death for market share, AI leadership, and global dominance. But the real story, the brutally honest one, is far more interesting. In the world of AI infrastructure, NVIDIA, Microsoft, and Google are not just competitors… they’re completely dependent on each other.
They compete and collaborate, fight and fuel one another, challenge and lock each other into billion-dollar cycles.
This is the hidden truth:
None of the three can win the AI future alone.
Their strategies and revenue pipelines are tightly linked.
This article explains in simple, human language how NVIDIA, Microsoft, and Google work together, why they need each other, and how this collaboration quietly locks in massive future revenue for all three.
Let’s break it all down clearly and honestly.
The First Truth NVIDIA Sells the “Picks and Shovels” of the AI Gold Rush
Before we explain how the trio works together, you need to understand one thing:
NVIDIA is the foundation.
Every large AI system in the world from ChatGPT to Google Gemini to Microsoft Copilot runs on NVIDIA GPUs.
Not Intel, AMD (not at scale), Apple Silicon. or even the custom chips (not yet).
NVIDIA is the de facto standard for AI compute.
Why?
Because NVIDIA dominates in three ways:
1. Hardware Power (GPUs)
NVIDIA’s H100, H200, B100, and upcoming X100 chips are the most powerful AI accelerators in the world. Cloud companies need them. AI companies need them. Enterprises need them.
No other chipmaker matches NVIDIA’s performance + software ecosystem.
2. CUDA (NVIDIA’s moat)
CUDA is NVIDIA’s software platform developers build AI models on top of it.
Once you build on CUDA, switching away is almost impossible.
This is the biggest lock-in inside AI infrastructure.
3. Supply + Scale
NVIDIA owns the entire AI hardware demand curve.
If you want to train an AI model, you need NVIDIA.
Period.
Now here’s the part most people miss…
**NVIDIA does not deploy the world’s AI.
Microsoft and Google do.**
This is where the relationship becomes intertwined.
Microsoft and Google Are NVIDIA’s Biggest Customers And Also Its Biggest Amplifiers
Let’s be brutally honest:
Microsoft Azure and Google Cloud cannot function without NVIDIA.
Both companies spend billions per year buying NVIDIA GPUs to power their cloud AI services.
Microsoft Azure AI = NVIDIA GPUs
Google Cloud Vertex AI = NVIDIA GPUs
Without NVIDIA:
• Azure’s AI business collapses
• Google Cloud’s AI revenue collapses
• ChatGPT cannot run
• Gemini cannot run
• Enterprise AI workloads die
This is why Azure, GCP, and AWS fight for GPU allocation like it’s gold.
NVIDIA sells the shovels.
Microsoft and Google sell the gold mining land.
Their relationship is symbiotic:
NVIDIA makes money from selling GPUs.
Microsoft + Google make money from renting them out.
How Microsoft Uses NVIDIA to Lock In Future Revenue
Microsoft’s AI business relies on a simple economic ladder:
Step 1 Microsoft buys NVIDIA GPUs.
Microsoft invests billions into GPU clusters (tens of thousands of H100s, B100s, and more).
Step 2 It rents these GPUs to enterprises at a markup.
Companies like Coca-Cola, Walmart, JP Morgan, Procter & Gamble pay per hour, per token, or per seat.
Azure becomes profitable because NVIDIA exists.
Step 3 Microsoft builds AI services on top of NVIDIA GPUs.
Copilot
Copilot for Office
Copilot for Azure
GitHub Copilot
Dynamics AI
Security AI
Teams AI
Windows AI
Every one of these services relies on NVIDIA GPU compute.
Step 4 Enterprises get locked into Microsoft AI.
Once a business builds:
• internal AI models
• data pipelines
• Office workflows
• cloud infrastructure
• security layers
…switching away becomes painful and expensive.
GPU lock-in (NVIDIA) becomes cloud lock-in (Azure) becomes enterprise lock-in (Microsoft).
This is the hidden revenue chain.
Microsoft doesn’t make money selling GPUs.
It makes money renting NVIDIA power.
How Google Uses NVIDIA to Lock In Future Revenue
Google Cloud follows a similar playbook but with Google’s unique twist.
Google uses NVIDIA GPUs for:
• training Gemini
• serving Gemini
• powering Vertex AI
• running customer models
• powering AI search features
But Google also has an advantage:
Google owns YouTube, Search, Android, Chrome all powered by AI.
NVIDIA’s GPU power → lets Google make AI-enhanced services → which increases ad revenue → which funds more NVIDIA purchases.
See the loop?
Google’s lock-in works like this:
1. Google Cloud hosts AI workloads (powered by NVIDIA).
Developers choose Vertex AI → adopt Google Cloud → commit long-term.
2. Google adds Gemini into Search, YouTube, and Android.
This increases user engagement → increases ad impressions → increases revenue.
3. Google invests more into AI → buys more NVIDIA GPUs → repeats.
A self-reinforcing cycle.
**NVIDIA fuels Google.
Google fuels demand for NVIDIA.
Both win.**
Why NVIDIA Needs Microsoft and Google (This Part Is Always Hidden)
You often hear that Microsoft and Google depend on NVIDIA.
But the reverse is equally true.
NVIDIA cannot sell GPUs without hyperscaler cloud platforms.
Hyperscalers =
Azure
Google Cloud
AWS
These companies buy 70%+ of NVIDIA’s total AI GPU output.
Why?
Because only hyperscalers have:
• giant data centres
• global distribution
• massive AI demand
• multi-billion budgets
• enterprise customers
NVIDIA does not run cloud businesses.
It cannot deploy GPUs globally, and does not sell directly to enterprises.
It needs Microsoft and Google to distribute the compute.
This creates a rare situation:
**NVIDIA controls the hardware.
Microsoft and Google control the deployment.
Both need each other to survive.**
The 3-Layer AI Infrastructure Stack (Simple Explanation)
The AI world is built on three layers:
Layer 1 Hardware (NVIDIA)
GPUs
Networking
HBM memory
Racks
NVLink
DGX systems
SuperPOD clusters
This is the AI engine.
Layer 2 Cloud Platform (Microsoft & Google)
Azure AI
Google Vertex AI
Google Cloud Run
Microsoft Fabric
Azure Machine Learning
This is the AI delivery system.
Layer 3 AI Services + Apps (Microsoft & Google)
Microsoft 365 Copilot
GitHub Copilot
Bing Chat
Google Gemini
YouTube AI
Android AI
Google Workspace AI
This is the AI experience layer.
How This Creates Billion-Dollar Lock-In for All Three
Let’s connect everything together.
When a company (e.g., a bank, hospital, government agency) builds an AI solution, it typically uses:
• NVIDIA GPUs →
• on Microsoft Azure or Google Cloud →
• running Microsoft or Google AI tools →
• integrated into Microsoft 365, Google Workspace, or custom systems
Once all of that is set up…
It becomes extremely difficult to switch to a different provider.
Why?
Because switching means:
❌ retraining models
❌ rebuilding data pipelines
❌ rewriting applications
❌ migrating storage
❌ setting up new security
❌ new contracts, SLAs, compliance
❌ downtime + risk
Enterprises avoid all of that.
So they stay.
Year after year.
Contract after contract.
Renewal after renewal.
This means:
**NVIDIA gets recurring GPU demand.
Microsoft gets recurring Azure + Copilot revenue.
Google gets recurring Vertex + AI service revenue.**
This is what “AI infrastructure lock-in” really means.
It’s not about “GPU shortages, “AI model wars” or even about “who has the best chatbot.”
It’s about:
• who controls the compute
• who controls the platform
• who controls the ecosystem
• who controls the long-term customer relationship
And right now?
NVIDIA
Microsoft
Google
— control all three together.
The Brutally Honest Economic Reality
Here’s the truth big tech won’t say out loud:
⭐ **NVIDIA makes money upfront.
Microsoft and Google make money forever.**
NVIDIA sells the “car.”
Microsoft and Google sell the “ride.”
Every single day.
NVIDIA revenue = hardware sales (huge one-time orders).
Microsoft + Google revenue = cloud subscriptions (recurring for years).
All three companies benefit but in different ways:
NVIDIA
• sells GPUs at massive margins
• locks in CUDA ecosystem
• ensures future demand
Microsoft
• becomes the AI operating system for enterprises
• locks in Azure consumption
• sells Copilot across every Microsoft product
• drives AI-powered search + ad revenue
• grows Google Cloud
• integrates Gemini across Android + Workspace
This triangle is the backbone of the global AI economy.
Final Thoughts These Three Companies Define AI’s Next 20 Years
People think AI competition is chaotic.
In reality, the relationships are highly structured.
The honest truth:
**NVIDIA builds the power.
Microsoft and Google distribute the power.
Enterprises get locked into the power.**
Everyone wins except smaller competitors who can’t match this scale.
NVIDIA needs Microsoft + Google.
Microsoft + Google need NVIDIA.
And customers need all three.
This is why the trio will dominate:
• cloud AI
• enterprise AI
• GPU demand
• AI services
• long-term revenue pipelines
And unless something dramatic changes, the next decade of AI will be defined by this triangle of power.