The Hidden Cost of DIY RAG: Why 42% of Enterprise AI Initiatives Were Scrapped in 2025

There is a story that repeats itself in enterprise technology teams with quiet, expensive regularity. A senior leader sees a compelling demo. A proof-of-concept gets green-lit. Engineers are excited. A small team spends weeks wiring together a retrieval pipeline, a vector store, an embedding model, and a prompt layer.

In the test environment, things seem great. But when the project hits production, it falls apart due to messy real-world data.