AI Market Map 2026
A comprehensive market map for AI investors.
The AI Stack
┌─────────────────────────────────────────────────────────┐
│ 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 training
- AMD: ~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 software
- Technology trajectory - Custom silicon?
For Application Investments
- Workflow depth - How embedded in customer ops?
- Retention - Are users staying?
- Gross margin - 70%+ software threshold
- Defensibility - Data? Brand? Network effects?
For Model Investments
- Compute efficiency - Token per dollar
- Developer ecosystem - How many building on it?
- Safety - Evaluation methodology
- Business 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
Last updated: February 2026 - Updated weekly