AI Business & Monetization
Where the Money Is in AI Right Now
Nvidia is worth $3T - more than the entire economy of France. Midjourney earns $200M profit with a team of 40. Cursor grew to $100M ARR in 2 years. These are all AI businesses that appeared recently. The question is: where does a new entrant fit in this revolution?
- Nvidia: GPU monopoly brought $80B revenue in 2024 - 122% growth year over year
- OpenAI: $3.4B ARR at 300% growth, but still unprofitable due to inference costs
- Midjourney: bootstrapped without VC, $200M pure profit, 40 employees
- Cursor: AI code editor, $100M ARR - 100M users simply switched from VS Code
Real Numbers: Who's Making What
The AI market will reach $500B by 2030. But that's abstract. Let's look at specific companies with specific money right now.
- Nvidia: $80B revenue in 2024, 55% margin - selling shovels during a gold rush
- OpenAI: $3.4B ARR in 2024, growing 300% year-over-year
- Midjourney: $200M profit with a team of 40 people - pure profit, no VC
**The AI market isn't a bubble - it's a redistribution.** The money is real, but it's not evenly distributed. Profiting from it requires understanding exactly where it concentrates.
| Company | Metric | Value (2024) | Business Type |
|---|---|---|---|
| Nvidia | Revenue | $80B / year | GPU infrastructure |
| Microsoft Azure AI | AI revenue | $13B / year | Cloud + models |
| OpenAI | ARR | $3.4B | Foundation model + API |
| Anthropic | ARR | $1B+ | Foundation model + API |
| Midjourney | Profit | $200M / year | Application (image AI) |
| Cursor | ARR | $100M+ | Application (dev tools) |
| Perplexity | ARR | $100M+ | Application (search AI) |
| Jasper AI | ARR | $75M | Application (marketing) |
**Now is the perfect time to enter.** Early players (2020-2022) built the technology. Now (2024-2026) is the market validation period: customers are ready to pay, competition isn't yet cutthroat. By 2028, most niches will be taken.
Midjourney earns $200M profit with a team of 40 people. OpenAI has $3.4B ARR with thousands of employees and is still unprofitable. What does this tell us about the business model?
Three Pyramid Layers: Where Margins Are Higher
**The AI industry has a clear structure** - three layers, each with its own economics, entry barriers, and margins. Understanding this structure means understanding where to look for money.
| Layer | Margin | Entry Barrier | Capital to Start | Who Wins |
|---|---|---|---|---|
| Infrastructure (GPU, Cloud) | 55-70% | Massive | $100M+ | Corporations, governments |
| Foundation Models | 20-40% | Very high | $50M+ | Well-funded startups |
| Applications | 60-80% | Low | $0-$1M | Indies, startups, corporates |
**The Midjourney paradox:** their margin is higher than Stability AI (200+ employees) because Midjourney doesn't build infrastructure - they buy GPU time from AWS, use open weights (Stable Diffusion), and focus on where value is really created for users: UX, prompt engineering, community.
**The middle layer trap:** foundation models look attractive, but this is the most expensive and competitive segment. OpenAI loses money at $3.4B ARR - inference is expensive. Entering without $50M+ is practically impossible.
Why does the Application layer have 60-80% margins even though foundation models build the actual technology?
Opportunity Map: What's Undervalued Right Now
**Saturated markets** - many competitors, little differentiation, price wars. **Undervalued niches** - high pain, willingness to pay, few quality solutions.
| Niche | Status | Why interesting / why not |
|---|---|---|
| General chatbot (GPT-wrapper) | SATURATED | ChatGPT already owns this, no differentiation |
| AI for SMB (small business) | HOT | ChatGPT is too complex, willing to pay $50-200/mo |
| Vertical AI for professions | HOT | Legal, medical, finance - premium pricing, low churn |
| AI workflow automation | HOT | Replace repetitive tasks, ROI is obvious for business |
| AI content tools (general) | SATURATED | Jasper, Copy.ai, Notion are already here |
| AI for niche industries | UNDERVALUED | Manufacturing, agriculture, blue collar - few players |
| AI coaching / education | HEATING UP | MindForge, Khanmigo - personalization = value |
| AI data analysis for SMB | HOT | Excel replacement with AI - huge market without quality solutions |
| AI infra for non-tech companies | UNDERVALUED | Implementing AI in corporates without a dev team |
**Actionable advice:** The best AI businesses of 2024-2025 are built on the principle of 'old pain + AI solution'. Find an industry known from the inside, identify the most painful task - and wrap it in an AI product with the right UX.
You want to create an AI product with minimal budget. Which approach is most promising?
Key Ideas
- AI market - $240B in 2024, growing 40%+ per year
- Three layers: Infrastructure (Nvidia), Foundation Models (OpenAI), Applications (Cursor)
- Application layer has 60-80% margins - higher than Foundation Models
- Low barrier to entry in Application layer: idea + API is enough
- Saturated niches: generic chatbots, general content tools
- Hot niches: vertical AI for professions, AI workflow automation, SMB tools
What's Next
Now the landscape is clear. The next step is understanding the math of the value chain: from $1 of GPU time to a $20/month subscription.
- AI Value Chain — The math of margins across layers
- Foundation vs Application — Why the wrapper strategy works
Вопросы для размышления
- In which industry does the team have deep domain expertise? What is the most painful task there that could be solved with AI?
- Starting an AI business today with $10K - which pyramid layer makes the most sense and why?
- Name 3 products from the opportunity table that seem most interesting. What do they have in common?