The innovation of technology, particularly Artificial Intelligence (AI), has rapidly changed the world. It is currently at a nascent stage worldwide in the construction industry throughout the lifecycle of projects. However, construction organisations of developing countries such as South Africa are still lagging in recognising the need to adopt emerging digital innovations such as AI to improve the built sector’s performance. This study aims to identify organisational factors imperative to driving the adoption of AI in construction organisations. The study uses a quantitative survey approach to collect data through snowball sampling of industry experts on factors associated with AI adoption. With data from 169 respondents, exploratory factor analysis was adopted to identify critical organisational factors to ease AI adoption in the industry. Furthermore, confirmatory factor analysis was employed to demonstrate the relationship among the constructs. The study proposes 17 factors to drive organisational AI, categorised into four components; innovative organisational culture, competence-based development, collaborative decision-making, and strategic analysis. However, previous studies have identified organisational factors of AI in the construction and allied industries. This study presented the organisational factors of AI in the construction industry using EFA and CFA, a method not used in articles presented in the SLR identified. The use of CFA improves the measurement of the constructs. It thus enhances understanding of the underlying components of a construct and its relationship with AI in the construction industry.

Utilising emerging innovative technologies and systems to improve construction processes in an effort towards digitalisation has been earmarked as critical to delivering resilience and responsive infrastructure. However, successful implementation is hindered by several challenges. Hence, this study evaluates the challenges facing the adoption of unmanned aerial vehicles towards the digitalisation of the built environment. The study adopted a quantitative survey of built environment stakeholders in developed and developing economies. A total of 161 completely filled forms were received after the survey, and the data were analysed using descriptive analysis and inferential statistics. The study’s findings show that there are different barriers experienced between developed and developing countries in the adoption of drones towards digitalising construction processes in the built environment. Moreover, economic/cost-related factors were identified as the most critical barriers to the adoption of drones, followed by technical/regulatory factors and education/organisation-related factors. The findings can assist the built environment in reducing the impact of these barriers and could serve as a policy instrument and helpful guidelines for governmental organisations, stakeholders, and others.