Application Of Artificial Intelligence as An Agility Driver in Project Management

The dynamic and ever-evolving business landscape demands adaptability and responsiveness from project management approaches. Agile methodologies, with their emphasis on iterative development, continuous feedback, and team collaboration, have become the preferred approach for navigating uncertainty and achieving successful project outcomes. However, even Agile practices can face challenges in areas like resource allocation, risk prediction, and continuous improvement. Artificial intelligence (AI) offers a powerful set of tools to address these limitations and further enhance the agility of project management. This paper explores how AI can be leveraged as an agility driver in project management, specifically within the Agile framework. We review existing literature on the subject, examining how AI can be applied in various stages of the Agile lifecycle. We then discuss potential methodologies for integrating AI into Agile workflows, followed by a hypothetical scenario with numerical results showcasing the impact of AI on project efficiency. Finally, we conclude by summarizing the benefits and limitations of AI in Agile project management, highlighting areas for future research.The dynamic and ever-evolving business landscape demands adaptability and responsiveness from project management approaches. Agile methodologies, with their emphasis on iterative development, continuous feedback, and team collaboration, have become the preferred approach for navigating uncertainty and achieving successful project outcomes. However, even Agile practices can face challenges in areas like resource allocation, risk prediction, and continuous improvement. Artificial intelligence (AI) offers a powerful set of tools to address these limitations and further enhance the agility of project management. This paper explores how AI can be leveraged as an agility driver in project management, specifically within the Agile framework. We review existing literature on the subject, examining how AI can be applied in various stages of the Agile lifecycle. We then discuss potential methodologies for integrating AI into Agile workflows, followed by a hypothetical scenario with numerical results showcasing the impact of AI on project efficiency. Finally, we conclude by summarizing the benefits and limitations of AI in Agile project management, highlighting areas for future research.

Keywords:

Artificial Intelligence , Agility , Project Management , Machine learning , Prediction