<b>BRIDGING THE DIGITAL TRANSFORMATION GAP IN NIGERIA'S CONSTRUCTION INDUSTRY: CHALLENGES FROM AI ADOPTION</b>

Nigeria's construction industry remains largely disengaged from artificial intelligence (AI) and machine learning (ML) tools despite their demonstrated transformative impact globally. This systematic review synthesises evidence from 20 peer-reviewed, Scopus-indexed studies published between 2018 and 2024 to identify, classify, and analyse the specific barriers impeding AI adoption in the Nigerian construction sector. Unlike prior reviews that conflate BIM and general digitisation with AI adoption, this study explicitly distinguishes AI-specific constraints, including the absence of localised training datasets, algorithmic transparency deficits, and high computational costs, from generic technology adoption barriers. Guided by the Technology-Organisation-Environment (TOE) framework and a PRISMA-compliant search protocol, five interrelated barrier clusters emerge: AI-specific data and infrastructure constraints, human capital deficits, financial limitations, regulatory and governance voids, and organisational inertia. A multi-level, TOE-anchored intervention framework is proposed. The findings advance understanding of AI adoption in emerging economies and provide a theoretically coherent, evidence-based foundation for policy reform, industry strategy, and future empirical research in Nigeria's built environment.