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

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-30
DOI
https://doi.org/10.5281/zenodo.17197834
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
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article

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

Zenodo (CERN European Organization for Nuclear Research)
Statistical Distribution Estimation and Applications
article

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

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Toros University (TR)
Peace, Justice and strong institutions
Openalex Percentile: Top 41%
Statistical Distribution Estimation and Applications
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AI-augmented agile project management in engineering: A framework for smart decision-making and risk mitigation · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS