Algorithmic architecture has emerged as an innovative approach in contemporary design, utilizing algorithms and parametric computation to generate complex forms and optimize construction processes. However, the implementation of this method within Iran's traditional construction workshops faces significant challenges due to fundamental differences in building techniques, a lack of skilled labor, and resistance to technological innovation. This study aims to investigate the practical obstacles to applying algorithmic architecture in Iran's traditional construction context and to explore viable solutions that can bridge the gap between digital design and conventional building practices. The research seeks to identify the main barriers and assess how these can be addressed to support the integration of algorithmic methods into existing workflows. The methodology combines qualitative analysis and field-based inquiry. A theoretical foundation is established through a literature review of algorithmic design and international case studies. This is followed by semi-structured interviews with architects, engineers, and contractors working in traditional construction environments. Furthermore, case studies of semi-algorithmic projects in Iran are analyzed to gain insight into real-world challenges and adaptive strategies. Findings reveal that key barriers include technical constraints, inadequate training, high implementation costs, and cultural resistance. Nevertheless, practical solutions such as specialized training programs, the development of execution standards, and the use of hybrid (traditional–algorithmic) approaches can significantly reduce these obstacles. This research contributes a localized framework for adapting algorithmic architecture to Iran's traditional construction sector. By aligning digital design tools with on-the-ground realities, the study offers actionable strategies to support the digital transformation of the country's building industry.