AI and Machine-Learning Readiness of Project Management Information Systems in Finnish Construction: A Literature Review and Interview Study
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This thesis focuses on AI and machine-learning preparedness of project management information systems in Finnish construction. The gap in the existing research and practice is addressed in the study: although the use of PMIS is widespread, and the number of applications related to AI is increasing, the level of preparedness of existing PMIS environments to support AI and machine learning in real construction projects remains little known. The research is based on a systematic literature review, as well as a qualitative interview study of nine construction professionals in Finland. The literature review helped identify key dimensions of readiness, and the interview data were analyzed thematically using NVivo. The findings suggest that PMIS preparedness for AI/ML in construction in Finland is neither complete nor absent, but partial and uneven. A partial foundation already exists in the form of digital tools, formal documentation practices, reporting environments and early uses of AI assistance. Nevertheless, preparedness is hampered by disjointed system landscapes, incomplete information streams, coexisting formal and informal communication habits, uneven trust in project information, unresolved governance challenges, and inconsistent organizational routines, support, and workflow fit. The current AI applications in project work are primarily restricted to narrow assistive activities like summarization, drafting, search and other support functions that are under human control. The thesis finds that PMIS in Finnish construction are moving toward AI/ML readiness, although they are currently better suited to assistive use than to a more integrated, AI-enabled PMIS capability. The next level of development will be based on the advancement of system integration, data quality and standardization, governance, trust, and alignment of digital tools with the practical project workflow.