A comprehensive market map for AI investors.
The AI Stack
📋 Copy ┌─────────────────────────────────────────────────────────┐
│ APPLICATION LAYER │
│ (ChatGPT, Claude, Cursor, Perplexity, Midjourney) │
├─────────────────────────────────────────────────────────┤
│ MODEL LAYER (APIs) │
│ (OpenAI, Anthropic, Google, Meta, Mistral) │
├─────────────────────────────────────────────────────────┤
│ INFRASTRUCTURE LAYER │
│ (NVIDIA, AWS, GCP, Azure, CoreWeave, Together) │
└─────────────────────────────────────────────────────────┘Detailed Market Sizing
Training Infrastructure ($50B TAM)
Segment Market Size Growth GPU Servers $35B 40% YoY Networking $10B 30% YoY Storage $5B 25% YoY
Inference ($80B TAM)
Segment Market Size Growth Cloud Inference $50B 60% YoY Edge Inference $20B 100% YoY On-prem $10B 30% YoY
AI Software ($120B TAM)
Segment Market Size Growth Enterprise AI $60B 50% YoY Consumer AI $30B 80% YoY Developer Tools $30B 60% YoY
Infrastructure Layer
GPU Market
NVIDIA : ~95% market share in AI trainingAMD : ~5% (MI300X gaining)Intel : <2% (Gaudi)
Cloud AI
Provider AI Revenue Market Share AWS ~$10B 40% Azure ~$5B 25% GCP ~$5B 25% Others ~$2B 10%
Inference Companies
Company Specialty Throughput Together AI Open models 100K tok/s Fireworks Fast API 200K tok/s Anyscale Ray Varies Baseten Serverless 50K tok/s
Foundation Models
Model Comparison
Model Context Price Strengths GPT-5 1M $15/1M Ecosystem, reasoning Claude 4.6 1M $15/1M Safety, coding Gemini 2 2M $1.25/1M Multimodal, speed Mistral 3 128K $0.40/1M Open weights Llama 4 1M Open Open source
Model Pricing Trends
2024: $60/1M tokens (GPT-4)
2025: $15/1M tokens (GPT-4o)
2026: $1-2/1M tokens (commoditization)
Application Layer
Enterprise Applications
Category Leaders ARR Growth Copilot Microsoft $5B+ 200% Notion AI Notion $500M+ 150% Salesforce Einstein Salesforce $2B+ 50%
Consumer Applications
App Users Revenue Growth ChatGPT 200M+ $500M+ 100% Claude 10M+ $100M+ 300% Midjourney 20M+ $200M+ 100%
Key Investment Frameworks
For Infrastructure Investments
Compute scarcity - Who has GPU access?Ecosystem lock-in - CUDA, Kubernetes, etc.Margins - Hardware vs softwareTechnology trajectory - Custom silicon?
For Application Investments
Workflow depth - How embedded in customer ops?Retention - Are users staying?Gross margin - 70%+ software thresholdDefensibility - Data? Brand? Network effects?
For Model Investments
Compute efficiency - Token per dollarDeveloper ecosystem - How many building on it?Safety - Evaluation methodologyBusiness model - API vs enterprise
Risk Factors
Technical Risks
Risk Likelihood Impact Model commoditization High High GPU shortage Medium High Compute cost burden High Medium
Business Risks
Risk Likelihood Impact Customer concentration Medium High Regulatory Medium Medium Competition High High
Due Diligence Checklist
Resources
More AI Resources
Last updated: March 2026 - Updated weekly