In addressing the limitation of the analytic hierarchy process (AHP) in construction risk assessment and its inability to provide self-feedback connections in the risk, a combined approach of interpretive structural modeling (ISM) and analytic network process (ANP) for evaluating risks was proposed for intelligent construction applications. Firstly, based on the application of intelligent construction in building projects, the process was categorized into four stages: architectural design, material design, structural design, and construction management. An integrated evaluation index system was established by identifying eleven risk factors. Subsequently, a multi-layered hierarchical structure model of risk factors in intelligent construction applications was developed using interpretive structural modeling (ISM). Secondly, ANP was used to establish and solve the weight model for each risk factor and determine the indicator weights and rankings. This approach allows for the risk assessment of the intelligent construction process. Finally, the ranking revealed that the three most critical risk factors in the intelligent construction process were ethical oversight risks, human-machine distrust, and technological security vulnerabilities. The assessment outcomes of the model were consistent with the actual conditions of intelligent construction, thereby validating the model’s effectiveness and reliability. This provides a theoretical foundation for establishing and refining risk assessment models and frameworks in the promotion of intelligent construction.