AI-Driven Project Management in Real Estate Startups: An Exploratory Study of Sustainable Adoption in Ghana's Emerging Market

This study investigates the adoption and impact of artificial intelligence (AI) in project management within real estate startups in Ghana’s emerging market. Using a quantitative cross-sectional survey design, data were collected from 120 industry stakeholders, including project managers, founders, investors, engineers, and regulators.

The study examines key constructs such as project performance, AI implementation challenges, AI effectiveness, and strategic enablers. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were used to validate the measurement model, while Structural Equation Modelling (SEM) was employed to analyze the relationships between variables.

The findings reveal that reducing barriers to AI adoption, such as cost, data limitations, skill gaps, and integration challenges, has the most significant impact on improving project performance. While AI effectiveness and strategic enablers show positive relationships, their direct effects are not statistically significant, suggesting indirect pathways.

The study provides an empirically validated framework for AI-driven project management tailored to real estate startups in emerging markets. It offers practical insights for policymakers, practitioners, and investors seeking to enhance project delivery and sustainability through AI adoption.

 

This thesis is shared for academic dissemination. Portions of this work may be revised and submitted for publication in peer-reviewed journals.