AI-Based Prediction of Scope Creep in Agile Projects
Keywords:
Scope creep, Agile Software Development, Artificial Intelligence, Machine Learning, Project Risk Management, Predictive Analytics.Abstract
Scope creep is continuing to be one of the main challenges for Agile software development, usually preventing the projects from being timely completed, as well as causing them to go over budget and reduce product quality. New advances in artificial intelligence (AI) and machine learning have shown promise in forecasting and managing scope creep by monitoring project data, team actions, and risk factors. This document presents a thorough summary of AI usage to scope creep prediction in Agile projects. We comprehensively examine existing machine learning models for effort estimation, risk management, and scope management and uncover methods such as neural networks, deep learning, and ensemble learning. The examination consolidates findings of prominent studies in Agile project risk prediction, automated scope creep detection, and AI-enhanced scheduling and presents their efficacy and limitations. Besides, we identify challenges in the implementation of AI in Agile methods and propose future research areas to increase prediction accuracy and deployment in practice. This survey aims to provide researchers and practitioners with a shared understanding of AI usage in preventing scope creep, thus enhancing Agile project success.
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