Abstract
This study examines the impact of risks controlled by AI on the sustainable performance of the building sector in Jordan. 240 responses were obtained using the survey method from March to May 2024, while respondents from different positions, the size of the company, and demography for a wide representation. The analysis was performed by partial modeling of the struc-tural equation of the smallest squares (PLS- SEM), with robustness secured by sufficient sample size. Results show that risk management- supported AM is a significant entry on sustainable development goals (SDG) when applied in operation. The study finds that it mediates the indirect effect of risk management between AI adoption and SDG, where it examines its role in con-tributing to responsible growth. The article deals with space in the field of research by exploring how AI allows sustainability in construction projects, a relatively insufficiently explored area. The findings show the impact of AI on the life cycles of the project¿planning, implementation, and control¿improved efficacy, reduced risks, and guaranteed sustainability. These findings offer special guidelines in AI mapping using sustainability and innovation goals.
