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ISSN Approved Journal || eISSN: 2582-8185 || CODEN: IJSRO2 || Impact Factor 8.2 || Google Scholar and CrossRef Indexed

Fast Publication within 48 hours || Low Article Processing Charges || Peer Reviewed and Referred Journal || Free Certificate

Research and review articles are invited for publication in January 2026 (Volume 18, Issue 1)

AI-augmented agile project management in engineering: A framework for smart decision-making and risk mitigation

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  • AI-augmented agile project management in engineering: A framework for smart decision-making and risk mitigation

Chapal Barua 1, Jesmin Ul Zannat Kabir 2, Kazi Rezwana Alam 3, Ashrafur Rahman Nabil 4 and Sonay Duman 5, *

1 Central Michigan University, MSA in Engineering Management, Michigan, USA. 

2 Central Michigan University, MSA, IT Project Management, Michigan, USA. 

3 Central Michigan University, MSA IT Project Management and Engineering Management, Michigan. 

4 St. Francis College, MS in Information Technology Management, Brooklyn, New York, USA. 

5 Department of Software Engineering, Toros University, Mersin, Turkey. 

Research Article

International Journal of Science and Research Archive, 2025, 15(03), 967-973

Article DOI: 10.30574/ijsra.2025.15.3.1828

DOI url: https://doi.org/10.30574/ijsra.2025.15.3.1828

Received on 04 May 2025; revised on 12 June 2025; accepted on 14 June 2025

The study analyzed how Artificial Intelligence-driven decision-making might enhance agile project management. The use of Artificial Intelligence provides predictive analytics, real-time risk assessment. Decision making is driven by data, which increases the flexibility and efficiency of the project. This research proposed a framework that may optimize the effectiveness of Agile processes. All this is made possible by using Artificial Intelligence methods such as intelligent automation, machine learning, and natural language processing. The study highlights how Artificial Intelligence may enhance sprint planning. Impact of AI on backlog prioritizing, and resource allocation is also considered. This is accomplished via use of early detection and scenario analysis. The potential of Artificial Intelligence to transform project management in dynamic contexts is examined, along with its future implications for agile techniques in engineering.

AI-Driven; Decision Making; Real Time Risk Assessment; Data Driven Decision Making

https://journalijsra.com/sites/default/files/fulltext_pdf/IJSRA-2025-1828.pdf

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Chapal Barua, Jesmin Ul Zannat Kabir, Kazi Rezwana Alam, Ashrafur Rahman Nabil and Sonay Duman. AI-augmented agile project management in engineering: A framework for smart decision-making and risk mitigation. International Journal of Science and Research Archive, 2025, 15(03), 967-973. Article DOI: https://doi.org/10.30574/ijsra.2025.15.3.1828.

Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

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