Artificial intelligence in achieving carbon-neutral buildings: a critical analysis of the emerging techniques, their applications and challenges

Given the increasing energy consumption and carbon emissions within the building sector, developing carbon-neutral buildings (CNB) has become essential in recent times. To further advance the development of CNB, the use of Artificial Intelligence (AI) technologies has been considered beneficial. This paper aims to explore the application of AI in achieving CNB by focusing on emerging techniques, their applications/functions in achieving CNB, and their associated challenges. The current study employs a mixed method of literature review using both bibliometric and systematic reviews. Based on the 77 selected journal articles analysed, the results show 35 emerging AI tools for delivering CNB. Further, 30 barriers to AI adoption in delivering CNB were explored using the Technological-Organizational-Environmental framework. Major barriers include lengthy computational times, high operational complexity, large datasets, limited human resource skills, and high costs. The outputs of this study will inform practitioners on the key AI tools to consider when developing CNB. More importantly, the findings will serve as a basis for formulating relevant hypotheses for further empirical investigations.