Completion Date
Spring 6-11-2024
Document Type
Thesis
Degree Name
Master of Science (MS)
Program or Discipline Name
Project Management
Secondary Program or Discipline Name
Project Management
First Advisor
Dr. Sarah Dyson
Second Advisor
Dr. Ella Ponsford-Gullacci
Abstract
The ongoing difficulty in project management in achieving desired outcomes is frequently linked to the "value gap" that appears between program installation and execution, where stakeholders find it difficult to adjust actions to achieve desired outcomes. Adaptable tactics are required to overcome the challenges posed by a various of interests, decision-making procedures, and resource limitations in traditional stakeholder engagement approaches. This study aims to know the key factors that influence the acceptance of AI-driven forecasting in project management processes for stakeholder management, and how these characteristics help to overcome the drawbacks of conventional stakeholder engagement approaches. The paper investigates the revolutionary potential of AI-driven forecasting in closing the value gap through an extensive examination of the literature. By utilizing AI-driven predictive modeling and analyzing current literature, the research endeavors to offer practical solutions for enhancing project success and deepening our comprehension of stakeholder involvement. Stakeholders can enhance the dynamic field of project management by adopting AI technology, enabling them to address obstacles, optimize resource allocation, and promote collaborative interactions.
Recommended Citation
Hasan, R. (2024). Enhancing stakeholder engagement in project management through ai-driven predictive modeling. Retrieved from https://digitalcommons.harrisburgu.edu/dandt/22