The article argues that traditional knowledge‑base approaches and AI‑generated queries cannot meet B‑enterprise requirements, presents low success rates for complex queries, and shows how the Model Context Protocol (MCP) delivers on‑prem data access, standardized APIs, and 60‑75% lower operational costs.
The article analyzes the widening gap between massive AI investment and modest commercial returns, showing how cloud giants like AWS and Google Cloud face shrinking margins despite soaring capex, while consumer‑facing AI products such as ChatGPT struggle to convert billions of users into paying customers, highlighting systemic profitability challenges across both B2B and B2C AI markets.
The article analyzes why B2B large‑model projects often stall at demo, prototype, or POC stages and proposes a three‑level value‑lift framework—model domain intelligence, business‑process smart density, and pervasive seamless interaction—to turn demos into real‑world impact.
