AI低代码技术正处于从实验室创新向产业化应用跨越的关键窗口期。本文以电信运营商行业为观察样本，构建“技术突破—概念验证—中试平台—规模化部署”四阶段产业化路径模型并进行规模化实证。研究发现：AI低代码产业化的核心矛盾在于“工程化能力”与“规模化要求”之间的适配差距。在此基础上，分析全球产业化态势，从政策引导、平台建设、技术经理人培育等维度提出推进策略，为相关成果产业化提供路径参考。

AI low-code technology is at a critical window from laboratory innovation to industrial application. Taking the telecom operator industry as an observational sample, this paper constructs a four-stage industrialization path model of “technological breakthrough—proof of concept—pilot platform—large-scale deployment” and conducts empirical analysis. The core contradiction lies in the adaptation gap between engineering capability and scale requirements. Global industrialization trends are analyzed and promotion strategies proposed from policy guidance, platform construction, and technology manager cultivation, providing a reference for industrial transformation of related achievements.