AI BriefingThe Tooling Landscape Seen Through 200 AI Case Studies
Key point
An analysis of 200 real-world AI case studies maps out the tooling landscape and deployment structures.
Details
Classifying 200 real-world AI case studies revealed that enterprise AI stacks converge into a handful of categories.
- ML Platform ranked highest at 10.9%, including Amazon Bedrock, Google Vertex, IBM Watsonx, and NVIDIA Isaac Lab.
- CRM & Sales came in at 9.7%, Data Platform at 7.3%, Agentic Management at 7%, LLMs at 7%, and Developer Tools also at 7%.
- Business Intelligence, Security, Healthcare, and Chatbots were all under 3%, with chatbots increasingly being reclassified as agents.
Deployment structures broke down into Platform-first at 47%, API-first at 31%, and Hybrid at 22%.
The key point is that while LLMs dominate the headlines, they account for only 7% of actual deployment stacks. Real-world implementations are distributed not just across models but also data platforms, enterprise software, orchestration, and observability tools, with adoption moving fastest in Engineering and Operations, and in Tech and Finance.
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