Enterprises Favor RAG Over Fine-Tuning For Production

An industry analysis warns that while many AI projects reach proof-of-concept, nearly 80% fail to reach reliable production; it examines causes observed in enterprises (fine-tuning technical debt, reliability gaps, and high total cost of ownership) and contrasts fine-tuning with prompt engineering and retrieval-augmented generation (RAG). It recommends a '70% rule' favoring RAG-first architectures, traceability, guardrails, and human-in-the-loop workflows to lower maintenance costs and improve reliability.