Three independent research firms project the global AI market between $827B and $1.59T by 2030. The range reflects different scoping methodologies, but all three agree on 25-35% compound annual growth.
Of 326 indie AI projects with disclosed revenue, nearly half earn under $1,000/month. The top 1.2% — 4 projects — exceed $50,000/month. These aren't random; they're domain-specific tools with clear customer acquisition paths.
46% of projects earn $500–$1,000/month. The differentiator for the top earners is never the AI itself — it's the problem being solved and the specificity of the customer they serve. Generic wrappers account for the majority of the failure column.
Real products with confirmed revenue — not fundraising announcements or pitch deck projections.
| Product | Founder | Annual Revenue | Category | Team | Timeline | Status |
|---|---|---|---|---|---|---|
| Cursor | Anysphere | $1,000,000,000 | AI Code Editor | Small team | 17 months to $1B | Active |
| Lovable | — | $200,000,000 | AI App Builder | Small team | 8 months to $100M | Active |
| Photo AI | Pieter Levels | $1,656,000 | AI Photo Generation | 1 person | 18 months | Active |
| HeadshotPro | Danny Postma | $1,000,000+ | AI Headshots | 1 person | <12 months to $1M ARR | Active |
| Base44 | Maor Shlomo | $80,000,000 exit | AI App Builder | 1 person | Solo build to acquisition | Acquired |
| AutoShorts.ai | Eric Smith | $1,200,000+ | Video Automation | 1 person | $100K+ MRR achieved | Active |
| PDF.ai | — | $600,000 | Document Intelligence | 1-2 people | ~12 months | Active |
| Construction SaaS | "Marcus" | $660,000 | Vertical SaaS | 1 person | 400+ paying customers | Active |
| TypingMind | — | $396,000 | Custom AI Interface | 1 person | Ongoing growth | Active |
Current market rates for AI-related consulting and freelance work, stratified by experience tier. These rates reflect what people are actually charging and getting paid, not theoretical ceilings.
The structural economics problem with AI products: every customer interaction consumes API tokens. Traditional SaaS pays infrastructure once and serves at near-zero marginal cost. AI SaaS pays per inference. This compresses margins from 80-90% to 50-65%.
| Model | Input / 1M Tokens | Output / 1M Tokens | Avg Cost / Request | Monthly (10K req/day) | Batch Discount |
|---|---|---|---|---|---|
| Claude Haiku (fast) | $1.00 | $5.00 | $0.003 | $900 | 50% |
| Claude Sonnet (balanced) | $3.00 | $15.00 | $0.009 | $2,700 | 50% |
| Claude Opus (premium) | $5.00 | $25.00 | $0.015 | $4,500 | 50% |
Note: Prompt caching cuts input costs 90%. A small product on Haiku handling 10,000 daily requests costs $50–$150/month after caching. Price AI products at 3-5x API costs minimum to sustain margins.
| Statistic | Value | Source |
|---|---|---|
| Enterprise AI Adoption | 78% | McKinsey State of AI, 2025 |
| Companies Increasing AI Budget | 88% | PwC AI Survey |
| AI Talent Demand Ratio | 3.2:1 | Signify Technology |
| AI Startup Failure Rate | 90% | Multiple sources |
| Enterprise Pilot Failure Rate | 95% | MIT NANDA, Aug 2025 |
| Early Adopter ROI (per $1) | $3.70 | Deloitte |
| Top Performer ROI (per $1) | $10.30 | Deloitte |
| AI Market CAGR (2025–2030) | 30.6% | Grand View Research |
| AI Engineer Avg Salary | $206,000 | Coursera, 2025 |
| Prompt Engineer Median Salary | $126,000 | Industry surveys |
AI is a leverage tool, not a product category. It multiplies existing skills. The fastest path to revenue is domain expertise + AI acceleration — doing what you already know how to do, faster, better, at scale. The question isn't "can I make money with AI?" — it's "what do I know that most people don't, and can AI make that more valuable?"