Date: 2025-03-11

Degree: Doctoral Thesis

Programme: Doctor of Business Administration

Authors: Cao Wei

Supervisors: Professor Joao Alexandre Lobo Marques, University of Saint Joseph

VIEW RECORD IN LIBRARY >


Abstract:

Artificial Intelligence (AI) is being applied in different areas of Administration and Management including finance, e-commerce, etc. Project Management (PM) is one area that may benefit from the use of AI to support project managers in making more accurate predictions, more quickly, such as deadline adjustments and cost updates, while at the same time helping with some of repetitive tasks of PM by relieving managers from these processes. Nevertheless, multiple aspects are still in consideration to allow AI to be widely adopted in PM, including lack of validated systems, including aspects of quality and prevalence, trust from users, market and specialists, and how the government will play a role to support the wider adoption of AI tools. This research explores the integration of Artificial Intelligence (AI) in Project Management and its potential to enhance four aspects: service quality, trust, prevalence, and government support. The proposed methodology employs a systematic literature review (SLR) combining with a quantitative survey to assess the current state of AI in project management. The SLR covers scholarly articles from 2016 to 2021, focusing on AI’s impact on project management across various industries. The survey, conducted among 200 professionals, gathers insights into AI’s perceived benefits and challenges in project management. The research findings indicate a positive inclination towards AI in project management, with respondents recognizing its potential to improve efficiency, support data-driven decisions, and enhance risk management. However, the study also reveals concerns regarding data quality, privacy, and the need for ethical considerations in AI applications. Most respondents agree on the necessity of government support to foster AI adoption and the importance of establishing trust in AI systems through transparency and security measures. The thesis concludes with recommendations for practitioners and policymakers to effectively leverage AI in project management. It proposes a framework including the development of training programs, the establishment of quality standards for AI services, and the promotion of public-private partnerships to drive innovation. The study emphasizes the importance of a multi-faceted approach to AI integration, considering technological, organizational, and ethical dimensions.