Factors Influencing the Adoption of Artificial Intelligence Tools in Quantity Surveying Practice in Lagos State, Nigeria

Studies indicate that Artificial Intelligence (AI) has the potential to improve cost estimation, reduce waste, predict project delay, streamline tendering processes, and analyse large datasets to provide data-driven insights. While AI offers promising solutions, its adoption within the Quantity Surveying practice in Lagos State, Nigeria is still limited; hence, this study. This paper examines the factors inhibiting and promoting the adoption of artificial intelligence in Quantity Surveying (QS) practice in Lagos State, Nigeria. The study employed a quantitative research method. Out of a total of 125 Quantity Surveying firms identified as the sampling frame, 60% (equivalent to 75 firms) were selected using a random sampling technique to ensure fair representation of the whole population. The data were analysed using frequency distribution, mean score and ANOVA. The results reveal that high implementation costs, resistance to change, uncertainty about returns, skill shortages, and weak regulatory frameworks are the critical factors inhibiting the adoption of AI in QS practice, while improved accuracy in cost estimation, competitive advantage, and data-driven insights are the strongest promoters of the adoption of AI in QS practice. The study concludes that AI has strong potential to transform QS service delivery, but overcoming financial, institutional, and cultural challenges is essential for its full integration. Development of a Real-Time IoT-Based Air Quality