Analysis of the drivers and barriers influencing artificial intelligence for tackling climate change challenges

Purpose Facilities management (FM) organizations are pivotal in enhancing the resilience of buildings against climate change impacts. While existing research delves into the adoption of digital technologies by FM organizations, there exists a gap regarding the specific utilization of artificial intelligence (AI) to address climate challenges. This study aims to investigate the drivers and barriers influencing the adoption and utilization of AI by South African FM organizations in mitigating climate change challenges. Design/methodology/approach This study focuses on South Africa, a developing nation grappling with climate change’s ramifications on its infrastructure. Through a combination of systematic literature review and an online questionnaire survey, data was collected from representatives of 85 professionally registered FM organizations in South Africa. Analysis methods employed include content analysis, Relative Importance Index (RII), and Total Interpretative Structural Modeling (TISM). Findings The findings reveal that regulatory compliance and a responsible supply chain serve as critical drivers for AI adoption among South African FM organizations. Conversely, policy constraints and South Africa’s energy crisis emerge as major barriers to AI adoption in combating climate change challenges within the FM sector. Originality/value This study contributes to existing knowledge by bridging the gap in understanding how AI technologies are utilized by FM organizations to address climate challenges, particularly in the context of a developing nation like South Africa. The research findings aim to inform policymakers on fostering a conducive environment for FM organizations to harness AI in fostering climate resilience in built assets.