The roles of artificial intelligence and generative applications in project management: driving digital transformation and organizational effectiveness

Muhammad Muflih, Saide Saide, Aulia Kartika Dewi, Zhanar Baiseitova

2026

Closed access Metadata (CSL-JSON)
DOI 10.1108/ijmpb-09-2025-0356
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

Purpose While artificial intelligence (AI) promises enhanced automation and real-time insights, its effective integration across the project lifecycle remains uneven and fragmented. This review synthesizes current developments, trends, and challenges of AI integration within project management information systems (PMIS). The study reconceptualizes PMIS as a strategic decision infrastructure supporting digital transformation (DX). Design/methodology/approach This study adopts a mixed-methods research synthesis approach to based on 70 peer-reviewed publications published between 2015 and 2025. Quantitative analyses were used to examine publication trends, geographical distributions and research patterns, while qualitative thematic analysis was conducted to synthesize AI functions, benefits, challenges and implementation strategies across PMIS phases. PRISMA-based procedures were applied to ensure systematic study selection. Findings The review highlights the growing integration of AI across key PMIS functions, including intelligent scheduling, predictive risk forecasting, automated reporting, and decision support. AI adoption contributes to improved organizational efficiency and project governance; however, implementation remains uneven due to data quality limitations, fragmented digital ecosystems, and organizational resistance. The study also identifies the emerging role of Generative AI (GenAI) and positions AI as a “cognitive co-actor” within socio-technical project environments. Practical implications This study provides actionable recommendations for managers, PMIS developers and decision-makers. Findings emphasize the importance of workforce upskilling, data governance and aligning AI-enabled PMIS with broader DX strategies. Policymakers may also leverage the findings to support regulatory compliance and responsible AI governance initiatives. Social implications Responsible AI integration within PMIS can enhance transparency, support workforce reskilling and democratize access to intelligent project management tools. Originality/value This study develops an integrative lifecycle-based perspective that maps AI functionalities across PMIS phases while distinguishing between general AI applications and AI capabilities specifically embedded within PMIS environments. The findings contribute to the growing intersection of AI, project management and digital transformation research by providing a conceptual foundation for future AI-enabled PMIS studies.