AI in Software Engineering: A Survey on Project Management Applications
Talia Crawford, Scott Duong, Richard Fueston, Ayorinde Lawani, Samuel, Owoade, Abel Uzoka, Reza M. Parizi, Abbas Yazdinejad

TL;DR
This survey reviews how AI, especially machine learning, is applied to software engineering project management, highlighting current research, challenges, and future directions in integrating AI into this domain.
Contribution
It provides a comprehensive overview of existing AI applications in software project management and discusses future research opportunities and challenges.
Findings
AI has significant potential to improve software project management.
Current research is limited but growing in applying AI to this field.
Challenges include data quality, integration issues, and ethical considerations.
Abstract
Artificial Intelligence (AI) refers to the intelligence demonstrated by machines, and within the realm of AI, Machine Learning (ML) stands as a notable subset. ML employs algorithms that undergo training on data sets, enabling them to carry out specific tasks autonomously. Notably, AI holds immense potential in the field of software engineering, particularly in project management and planning. In this literature survey, we explore the use of AI in Software Engineering and summarize previous works in this area. We first review eleven different publications related to this subject, then compare the surveyed works. We then comment on the possible challenges present in the utilization of AI in software engineering and suggest possible further research avenues and the ways in which AI could evolve with software engineering in the future.
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Taxonomy
TopicsSoftware Engineering Techniques and Practices · Software Engineering Research · Software System Performance and Reliability
