Perceived Complexity or Real Barriers? Lessons Learned on BIM Adoption in the GenAI Era: The Case of Côte d’Ivoire

Implementing Building Information Modelling (BIM) remains a major challenge for modernizing the construction sector in Africa, where adoption still lags significantly behind that of developed countries. This situation is frequently attributed to the complexity of BIM, a notion that often combines both structural barriers and psychological apprehensions among construction stakeholders. The objective of this study is to analyze the factors explaining the low adoption of BIM in Côte d’Ivoire by distinguishing perceived complexity from actual barriers, while examining the potential of Generative Artificial Intelligence (GenAI) to reduce this perceived complexity and facilitate BIM adoption. Drawing on a mixed-methods approach, the study combines a literature review, a questionnaire survey administered to Ivorian construction professionals, LinkedIn polls, and a real-life case study. The collected data were analyzed using IBM SPSS Statistics in order to identify and rank the factors influencing BIM adoption. The findings reveal that although real barriers such as costs, skills shortages and the absence of regulatory frameworks remain significant, their effects are amplified by an exaggerated perception of complexity. Resistance to change, fear of digital tools and uncertainty regarding BIM benefits appear to play a major role in limiting adoption. The results therefore suggest that perceived complexity constitutes a critical explanatory factor alongside structural barrier. In this context, GenAI emerges as a promising catalyst for BIM adoption. By simplifying software interactions through natural language interfaces, automating repetitive tasks and supporting users in learning and decision-making processes, GenAI has the potential to reduce perceived complexity and facilitate digital transformation in the construction sector. The study concludes that combining BIM and GenAI could present a significant opportunity for accelerating the modernization of the construction industry in Côte d’Ivoire and, more broadly, across developing countries. A BIM-Integrated Artificial Intelligence Framework for Automated Design Specification Compliance and Monitoring in Construction O