Intelligent Technology and Project Management: A Systematic Literature Review
This paper presents a systematic literature review analyzing the intersection of intelligent technology and project management through empirical studies encompassing 53 peer-reviewed articles published between 2018 and 2024. The research aims to identify key themes, geographic distribution, author contributions, and future research directions in the field. The thematic analysis reveals five predominant categories: project complexity and theorizing, project governance and management, digitalization and technology, inter-organizational projects and networks, and agility and innovation. The geographic analysis indicates that Europe, particularly the United Kingdom, leads in research contributions, while North America and Asia show emerging but limited involvement. The author's contribution analysis highlights notable scholars who emphasize governance, sustainability, and digital transformation. Future research is expected to focus on intelligent technology-driven risk management, the integration of agile methodologies, and sustainability practices within project management frameworks. The findings underscore the transformative potential of intelligent technologies in enhancing project outcomes, emphasizing the need for robust governance and adaptability in project management practices. The study identifies critical gaps, particularly in the areas of public-private partnerships and cultural dynamics, suggesting avenues for future research to optimize the integration of intelligent technologies in project management. Overall, this review contributes to the understanding of how intelligent technology can reshape project management, providing a conceptual framework that integrates independent, dependent, intervening, and moderating variables to enhance project success in an increasingly complex environment.
Authors
- Ann Wamaitha
Publication Details
- Journal
- The International Journal of Humanities & Social Studies
- Published
- 2025-04-29
- DOI
- https://doi.org/10.24940/theijhss/2025/v13/i2/hs2502-008
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00