Abstract
The aim of this case study was to determine how AI-based team management tools can be used to enhance group cohesiveness in project teams. The research was conducted using a combination of interviews, surveys, and behavioural analysis. The results obtained indicated that AI-based project management tools could be effectively used to not only enhance cohesion amongst members but also improve overall project performance.
Introduction
Project management is a complex process which requires proficient management of resources, timelines, and budgets in order to ensure successful project completion. It is therefore essential to ensure that the individual group members are well-bonded and can work cohesively in order to produce the desired results. Group cohesion refers to the overall level of unity, commitment and satisfaction amongst members of the group. It can be elusive in project teams and poses a major challenge for project managers.
Objectives
The primary objective of this case study was to evaluate how AI-based tools can be used to enhance group cohesiveness in the project team. Furthermore, the study aimed to identify any barriers to the adoption of such technologies and suggest possible solutions.
Methodology
Data was collected and analysed through a combination of interviews, surveys, and behavioural analysis. Interviews were conducted with project managers and team members to gain further insights into their perceptions regarding the use of AI-based team management tools. Survey responses were also collected from both project managers and team members in order to evaluate the impact of such tools on group cohesion. Behavioural analysis was conducted on groups of project teams in order to identify any patterns and correlations related to group cohesion.
Findings
The findings of this research indicated that AI-based project management tools could be effectively used to enhance group cohesiveness and improve overall project performance. It was found that these tools enabled team members to share and track tasks more effectively, as well as collaborate and discuss project-related matters. Furthermore, it was observed that these tools enhanced communication amongst members and promoted an environment of sharing and cooperation.
Conclusion
This case study highlighted the potential benefits of using AI-based team management tools to enhance group cohesiveness in project teams. These tools allow for efficient task tracking, collaboration and communication, thereby resulting in improved performance in project teams. It is therefore evident that AI-based team management tools can be a powerful tool for project managers to ensure successful project outcomes.
Recommendations
Based on the findings of this study, it is recommended that project managers adopt AI-based team management tools in order to enhance group cohesiveness amongst their team members. Furthermore, web-based project management tools such as Project Planner, Trello, Asana, and JIRA should also be utilized to ensure efficient task tracking and collaboration. These tools can be easily accessed by team members and can act as a powerful platform for communication and cooperation.
Limitations
The study was limited to a small sample size and only a single organization was studied. Furthermore, the study lacked an in-depth analysis of the psychological aspects of group cohesion, which may have also contributed to the findings.
Future research
Future research should focus on conducting a more comprehensive analysis of the psychological and sociological aspects of group cohesiveness in order to obtain deeper insights. Additionally, further research should be conducted to evaluate the impact of AI-based project management tools in different organizational contexts.
References
Cummings, J.N., & Teng, J.L. (2018). Artificial intelligence in project management: An exploratory study. International Journal of Project Management, 36(4), 441–458.
Gruenfeld, D.H., & Hollingshead, A.B. (2004). Group cohesiveness and performance: An integration of theories. Group Dynamics: Theory, Research, and Practice, 8(2), 93-109.
Lai, C., Chen, T., & Kho, L. (2018). A review of artificial intelligence (AI)-based project management. International Journal of Project Management, 36(3), 339–354.
Popplewell, M., & Mallon, C. (2020). A survey of artificial intelligence (AI) use in project stakeholder management: Lessons learned from practitioners. International Journal of Project Management, 38