Hill, Natoya (2025) A systematic literature review: Exploring the integration of artificial intelligence in construction management. DSc thesis, Middle Georgia State University, USA.
Abstract
Artificial intelligence (AI) is progressively transforming the planning, execution, and monitoring of building projects. AI provides tangible advantages to an industry characterized by complexity and risk, ranging from the enhancement of decision-making processes to the improvement of site safety and efficiency. Notwithstanding this promise, extensive implementation remains inconsistent. Numerous companies encounter issues related to expenses, employee fear, and insufficient technological preparedness. This systematic literature review examines the integration of AI technologies—namely machine learning, predictive analytics, and AI-driven safety systems—into construction workflows. Utilizing the Technology Acceptance Model (TAM), the study examines how perceptions of utility and usability affect adoption trends. The results indicate that adoption can be facilitated through specialized training, gradual implementation tactics, and conducive policy environments. This review provides ideas that may enhance the integration of AI into construction management by addressing technological and organizational issues.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Floyd, Kevin |
| Index terms: | complexity, technology acceptance model, usability, machine learning, organizational issue, monitoring, systematic literature review, integration, decision-making process, workflow, efficiency, artificial intelligence, implementation |
| Subjects: | business, control systems, acoustic properties, decision analysis, contractual arrangements, systems engineering, management, artificial intelligence, performance management, research evaluation and metrics, organizational analysis, user-centered design |
| Topics: | Business Strategy, Procurement, Engineering Principles, Organizational Design, Research Practice, Risk Management, Design Practice, Quality Management, Digital Applications, Site Management |
| Descriptive scope: | 3 PCE |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here