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Main Authors: Burdakov, Alexey, Ahn, Max Jaihyun
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2506.02214
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author Burdakov, Alexey
Ahn, Max Jaihyun
author_facet Burdakov, Alexey
Ahn, Max Jaihyun
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2506_02214
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Is PMBOK Guide the Right Fit for AI? Re-evaluating Project Management in the Face of Artificial Intelligence Projects
Burdakov, Alexey
Ahn, Max Jaihyun
Software Engineering
Computer Vision and Pattern Recognition
D.2.9; I.4
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.
title Is PMBOK Guide the Right Fit for AI? Re-evaluating Project Management in the Face of Artificial Intelligence Projects
topic Software Engineering
Computer Vision and Pattern Recognition
D.2.9; I.4
url https://arxiv.org/abs/2506.02214