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部署壁垒:企业人工智能部署时代的诊断框架与工具

The Deployment Wall: A Diagnostic Framework and Instrument for Enterprise AI in the Deployment Era

Fabricio F. Costa

arXiv 2607.29089首次发表:更新:

AI 中文总结

该研究针对企业生成式AI试点落地难问题,提出部署壁垒诊断框架与工具,通过评估平台消除摩擦的能力,助力企业将AI平台决策从基准比较转向架构比较。

AI 中文摘要

企业在生成式人工智能(AI)上的投资一年内增至约370亿美元,然而独立实地研究发现,约95%的企业生成式AI试点项目未产生可衡量的损益影响。我们认为,主流解释——模型能力不足——是错误的,企业AI已进入部署时代,优势并非源于模型智能,而是源于消除有能力的模型投入生产所面临的组织和架构摩擦。基于软件工程领域关于技术债务和机器学习部署的文献,以及对独立实地研究的结构化综合,我们将诊断工作落地。我们引入三个关联构念和一个测量工具:部署壁垒,一个六阶段价值流失模型,可机械复现观测到的存活率;接缝指数,一个可复现的0-12分诊断工具,用于评估任何平台原生消除六种重复摩擦“接缝”的数量,而非将其留给采用者;部署债务,一个构念,将未解决的摩擦重新定义为复利式、可量化的负债。我们制定了带有证据锚点的评分协议,确保工具可一致应用,通过一个已完成的平台选择示例说明其应用,并推导了六个可证伪命题及验证该命题的研究议程。该框架将八位数的平台决策从基准比较转化为架构比较。

英文摘要

Enterprise investment in generative artificial intelligence (AI) tripled in a single year to roughly US$37 billion, yet independent field research finds that about 95% of enterprise generative-AI pilots deliver no measurable profit-and-loss impact. We argue that the dominant explanation--that models are not yet capable enough--is mistaken, and that enterprise AI has entered a Deployment Era in which advantage derives not from model intelligence but from the removal of the organizational and architectural friction that prevents a capable model from reaching production. Building on the software-engineering literature on technical debt and machine-learning deployment, and on a structured synthesis of independent field studies, we make the diagnosis operational. We introduce three linked constructs and one measurement instrument: the Deployment Wall, a six-stage value-leak model that mechanically reproduces observed survival rates; the Seam Index, a reproducible 0-12 diagnostic that scores any platform by how many of six recurring friction "seams" it removes natively rather than leaving to the adopter; and Deployment Debt, a construct that reframes unresolved friction as a compounding, quantifiable liability. We specify a scoring protocol with evidence anchors so the instrument can be applied consistently, illustrate it on a worked platform-selection example, and derive six falsifiable propositions with a research agenda for validation. The framework converts an eight-figure platform decision from a benchmark comparison into an architecture comparison.

Comments19 pages, 6 figures, 8 tables. Introduces the Deployment Wall framework, the Seam Index diagnostic instrument (with an evidence-anchored scoring protocol), and the Deployment Debt construct; includes six falsifiable propositions and a research agenda

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