Impact of Advanced AI in Predicting Software Project Failure Risks
DOI:
https://doi.org/10.56472/ICCSAIML25-164Keywords:
Artificial Intelligence (AI), Software Project Management, Project Failure Risks, Risk Prediction, Machine Learning, Deep Learning, Predictive Analytics, Project Risk Management, Software Engineering, AI EthicsAbstract
Software project management is often plagued by the challenge of predicting and mitigating failure risks. Despite various methods, predicting failure remains a complex task. This paper explores the impact of advanced artificial intelligence (AI) in predicting software project failure risks. It discusses the application of machine learning, deep learning, and other AI techniques in identifying potential risks, forecasting project outcomes, and improving overall risk management strategies. The paper highlights the advantages of AI, including increased accuracy, faster decision-making, and the ability to analyze vast datasets. However, challenges such as data quality, algorithm biases, and the interpretability of AI models are also addressed. The paper concludes by discussing future trends in AI and its growing role in software project management, suggesting avenues for further research in the field
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