Abstract
Nowadays, organizations are constantly evolving in the way they manage their projects while innovating and automating certain tasks and processes for a smoother transition of projects. This is being achieved through the integration of artificial intelligence (AI) and machine learning. AI is continuously driving businesses to success and modernizing the world of projects. The research is based on a global human capital management company as a case study to investigate the issues that they face to meet their software project deadlines and then proposing a framework using AI to overcome their challenges. The mixed methods research with both qualitative and quantitative design was opted for this research. A systematic literature review (SLR) was carried out initially to identify the challenges involved in meeting project deadlines as a primary method for data collection. Focus group interviews were then carried out to collect data from team members and project managers working on projects and facing challenges to meet project deadlines. The proposed AI framework was then evaluated and 72.7% of participants rated the framework as effective and were keen to integrate AI at their workplace for smooth transition of tasks. A final framework was then proposed after the feedback received from participants.
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References
Akgun, A. E. (2020). Team wisdom in software development projects and its impact on project performance. International Journal of Information Management, 228–243.
Bagchi, T. P., Sahu, K., & Jena, B. K. (2017). Why CPM is not good enough for scheduling projects. In 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 1748–1752).
Basirati, M. R., Otasevic, M., Rajavi, K., Bohm, M., & Krcmar, H. (2020). Understanding the relationship of conflict and success in software development projects. Information and Software Technology, 126.
Bordley, R. F., Keisler, J. M., & Logan, T. M. (2019). Managing projects with uncertain deadlines. European Journal of Operational Research, 291–302.
Cappelli, P., Tambe, P., & Yakubovich, V. (2018). Artificial intelligence in human resources management: Challenges and a path forward. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3263878
Chou, J. S., Lin, C. W., Pham, A. D., & Shao, J. Y. (2015). Optimized artificial intelligence models for predicting project award price. Automation in Construction, 54, 106–115.
Filippetto, A. S., Lima, R., & Barbosa, J. L. V. (2021). A risk prediction model for software project management based on similarity analysis of context histories. Information and Software Technology, 131.
Inaam, A. (2016). Research in social science: Interdisciplinary perspectives (p. 17).
Karenkamp, M., Rebstadt, J., & Thomas, O. (2020). Applications of AI in classical software engineering. AI Perspectives, 2. https://doi.org/10.1186/s42467-020-00005-4
Kunnathur, M. U. (2020). Applying artificial intelligence techniques in project management [Master’s in engineering and management]. https://doi.org/10.13140/RG.2.2.15113.39526
Lebedeva, A., & Guseva, A. (2020). Managing IT projects and evaluating their cost and complexity: State of the problem. In 2020 2nd International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA) (pp. 677–680).
Pimchangthong, D., & Boonjing, V. (2017). Effects of risk management practice on the success of IT project. In 7th International Conference on Engineering, Project, and Production Management (Vol. 182, pp. 579–586).
Relich, M., & Muszynski, W. (2014). The use of intelligent systems for planning and scheduling of product development projects. In 18th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems—KES2014 (pp. 1586–1595).
Shameem, M., Chandra, B., Kumar, C., & Khan, A. A. (2018). Understanding the relationships between requirements uncertainty and nature of conflicts: A study of software development team effectiveness. Arabian Journal for Science and Engineering, 43, 8223–8238.
Webber, S. S., Detjen, J., Maclean, L. T., & Thomas, D. (2019). Team challenges: Is artificial intelligence the solution? ScienceDirect, 62, 741–750. https://doi.org/10.1016/j.bushor.2019.07.007
Zhang, W., Yang, Y., Xiao, L., & Babar, M. A. (2015). Ant colony algorithm based scheduling for handling software project delay. In Proceedings of the 2015 International Conference on Software and System Process (pp. 52–56). https://doi.org/10.1145/2785592.2785603
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Sheoraj, Y., Sungkur, R.K. (2023). Using AI to Manage Project Deadlines—Case Study of a Global Human Capital Management (HCM) Software Company. In: Ranganathan, G., Fernando, X., Piramuthu, S. (eds) Soft Computing for Security Applications. Advances in Intelligent Systems and Computing, vol 1428. Springer, Singapore. https://doi.org/10.1007/978-981-19-3590-9_35
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DOI: https://doi.org/10.1007/978-981-19-3590-9_35
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