The AI industry is not one market. It is a stack of interlocking layers — hardware, infrastructure, platforms, models, services, and applications.
The companies winning are those able to integrate across multiple layers, creating compounding strategic advantages.
This framework maps how major players position themselves across the AI stack.
The deeper strategic principles behind vertical integration are explored in The Business Engineer: https://businessengineer.ai/
Layer 1: Hardware — The Silicon Foundation
COMPLETE integration with in-house TPU development, Pixel Neural Core, and AI accelerators.
This gives Google structural cost advantage and supply certainty.
OpenAI
LIMITED — partners with NVIDIA; no custom silicon.
Microsoft
MODERATE — Azure custom silicon emerging (Maia, Cobalt chips).
Meta
EMERGING — RTX-class research chips, VR/AR hardware, Ray-Ban Meta integration.
Amazon
SELECTIVE — Inferentia, Trainium chips for AWS; not full-stack across devices.
Anthropic
NONE — entirely dependent on cloud partners.
Apple
INTEGRATED — A-series and M-series Neural Engines deeply tied to on-device AI.
NVIDIA
DOMINANT — the hardware bedrock of the entire industry.
Vertical hardware economics and strategic moats are analyzed in The Business Engineer:
https://businessengineer.ai/
Layer 2: Infrastructure — Compute, Data Centers, Networking
COMPLETE — global DCs, networking, Kubernetes, AI-optimized cloud.
OpenAI
PARTIAL — Azure-exclusive partnership. Limited independence.
Microsoft
COMPLETE — global scale, enterprise security, integrated Azure infrastructure.
Meta
STRONG — hyperscale infrastructure supporting social-scale workloads.
Amazon
DOMINANT — AWS is the backbone of the global cloud.
Anthropic
DEPENDENT — AWS/GCP; infrastructure outsourced.
Apple
LIMITED — iCloud, Edge processing, privacy-centric design.
NVIDIA
INDIRECT — enables others; does not run hyperscale clouds.
The infrastructure layer is a key source of compounding advantage, expanded in The Business Engineer:
https://businessengineer.ai/
Layer 3: Platforms — ML Frameworks, Tooling, APIs
COMPLETE — TensorFlow, JAX, Keras, Colab.
OpenAI
STRONG — GPT API, Playground, fine-tuning.
Microsoft
STRONG — Azure AI services, Cognitive APIs, ML Studio.
Meta
OPEN — PyTorch as a global standard.
Amazon
GROWING — SageMaker and AWS AI tooling.
Anthropic
FOCUSED — Claude API, safety-research tooling.
Apple
ECOSYSTEM — CoreML, CreateML, MLX, Apple-specific tooling.
NVIDIA
FOUNDATIONAL — CUDA, cuDNN, TensorRT, Triton define the global “AI runtime.”
Platform-level moats are broken down in The Business Engineer:
https://businessengineer.ai/
Layer 4: Models — Foundation Models and Specialized AI
COMPLETE — Gemini, PaLM, Imagen, DeepMind research.
OpenAI
LEADING — GPT-4o, Sora, Whisper.
Microsoft
PARTNERSHIP — OpenAI models + internal research.
Meta
COMPETITIVE — Llama 3.1, multimodal research, open source leadership.
Amazon
EMERGING — Nova models, Titan family, model hub.
Anthropic
EXCELLENT — Claude 3.5, strong alignment research.
Apple
PRIVATE — on-device models, privacy-first design.
NVIDIA
SELECTIVE — NeMo models and enablement.
The model layer and its competitive physics are explained in The Business Engineer:
https://businessengineer.ai/
Layer 5: Services — Enterprise AI Solutions
COMPLETE — Gemini AI, VertexAI, enterprise APIs.
OpenAI
GROWING — OpenAI Enterprise, ChatGPT products, custom models.
Microsoft
COMPLETE — Azure OpenAI, Copilot family, Power Platform.
Meta
LIMITED — enterprise adoption still early.
Amazon
COMPREHENSIVE — AWS AI/ML, Bedrock, enterprise integrations.
Anthropic
SIMPLE — Claude API and enterprise-focused features.
Apple
INTERNAL — AI services are ecosystem-centric, not enterprise-focused.
NVIDIA
ENABLER — powers others’ enterprise AI.
Enterprise AI economics are examined in The Business Engineer:
https://businessengineer.ai/
Layer 6: Applications — End-User AI Products
COMPLETE — Search, YouTube, Gmail, Android, Workspace.
OpenAI
FOCUSED — ChatGPT, GPT Store, Canvas.
Microsoft
INTEGRATED — Copilot across Windows, Office, Teams.
Meta
SOCIAL — Facebook, Instagram, WhatsApp.
Amazon
FRAGMENTED — Alexa, retail, enterprise internal tools.
Anthropic
MINIMAL — application layer largely partner-dependent.
Apple
INTEGRATED — Siri, Photos, ecosystem apps.
NVIDIA
INDIRECT — gaming, GeForce Now, partners.
Application strategy and verticalization are covered in The Business Engineer:
https://businessengineer.ai/
What This Map Shows
1. Google and Microsoft are the most vertically integrated.
From chips to apps, both span the full stack.
2. OpenAI and Anthropic are dependent on hyperscalers.
This limits independence but accelerates deployment.
3. Meta plays strongest in platforms, models, and consumer scale.
4. Amazon leads in infrastructure but is weaker in models and apps.
5. Apple is building a privacy-centric, on-device vertical stack.
6. NVIDIA remains the foundational hardware layer for the entire industry.
Vertical integration dynamics and competitive flywheels are explained in The Business Engineer:
https://businessengineer.ai/
Conclusion — Vertical Integration Is the AI Moat
AI is not fought at one layer of the stack.
The winners are those who integrate enough layers to generate compounding feedback loops:
- hardware → lower cost
- infrastructure → scale
- platforms → developer lock-in
- models → differentiation
- services → enterprise reach
- applications → behavioral data
Understanding this architecture is essential for navigating the competitive landscape.
A deeper, systems-level analysis is available in The Business Engineer:
https://businessengineer.ai/
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