AI项目管理不能照搬传统框架，需针对性调整。
Is PMBOK Guide the Right Fit for AI? Re-evaluating Project Management in the Face of Artificial Intelligence Projects
- 识别PMBOK在数据管理、迭代开发上的不足
- 提出融入数据全周期与伦理考量的改进方案
- 适合从事AI研发的项目经理参考
本文批判性评估了项目管理知识体系（PMBOK）框架在人工智能（AI）软件项目中的适用性，指出其关键局限。与传统项目不同，AI项目高度依赖复杂数据、迭代实验和专业人才，同时面临显著伦理挑战。分析发现PMBOK在数据管理、迭代支持及伦理与跨学科问题指导方面存在空白。为此，建议整合数据生命周期管理，采用适合AI的迭代式项目管理框架，并将伦理考量嵌入项目规划与执行全过程。此外，还探讨了更契合AI动态探索特性的替代方法。旨在通过填补这些差距，提升AI软件项目的管理实践。
原文摘要 · Abstract (English)
This paper critically evaluates the applicability of the Project Management Body of Knowledge (PMBOK) Guide framework to Artificial Intelligence (AI) software projects, highlighting key limitations and proposing tailored adaptations. Unlike traditional projects, AI initiatives rely heavily on complex data, iterative experimentation, and specialized expertise while navigating significant ethical considerations. Our analysis identifies gaps in the PMBOK Guide, including its limited focus on data management, insufficient support for iterative development, and lack of guidance on ethical and multidisciplinary challenges. To address these deficiencies, we recommend integrating data lifecycle management, adopting iterative and AI project management frameworks, and embedding ethical considerations within project planning and execution. Additionally, we explore alternative approaches that better align with AI's dynamic and exploratory nature. We aim to enhance project management practices for AI software projects by bridging these gaps.
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