500+ GenAI Case Studies: What Companies Actually Ship
I curated 500+ real-world GenAI deployments across industries. The patterns are surprising — and most have nothing to do with chatbots.
The gap between AI hype and AI reality is enormous. To close it, I spent 6 months curating every real-world GenAI deployment I could find, verify, and categorize. The result: 500+ case studies across 40+ industries.
The Surprising Findings
1. Chatbots Are Less Than 15% of Deployments
The most common GenAI deployment is not a chatbot. It is document processing. Extracting data from invoices, contracts, medical records, and compliance documents is where the money is.
Microsoft tech: Azure AI Document Intelligence handles this at scale. Combined with Power Automate, you get end-to-end document workflows.
2. Internal Tools Outnumber Customer-Facing 3:1
Companies are deploying AI internally first. Knowledge management, code generation, meeting summarization, and internal search dominate the case studies.
Microsoft tech: Copilot for Microsoft 365 is the entry point. GitHub Copilot for developer productivity. Copilot Studio for custom internal agents.
3. The ROI Comes from Boring Use Cases
The highest-ROI deployments are not flashy. They are: email categorization, data entry automation, report generation, and compliance checking. Boring scales. Flashy demos.
4. Microsoft Is in 60%+ of Enterprise Deployments
Across the 500+ case studies, Microsoft technologies appear in over 60% of enterprise deployments. The combination of Azure AI, Copilot, and Power Platform covers the broadest surface area of any single vendor.
The Collection
The full collection is open source on GitHub: genai-llm-ml-case-studies. Each case study includes:
- Company and industry
- Use case description
- Technology stack
- Reported outcomes (where available)
- My analysis of the pattern
How I Use It
When a PE operating partner says "Show me what companies like ours are doing with AI," I filter the collection by industry, company size, and use case category. Instead of hypotheticals, I show them real deployments with real outcomes.
This is the difference between "AI could help you" and "Here are 12 companies your size that did exactly this and achieved exactly that."
Why It Matters
The GenAI market is drowning in vendor marketing and analyst predictions. What is missing is evidence. 500+ case studies is not comprehensive—but it is a start. And it is free.