كنفرانس بين المللی مهندسی صنايع و سيستم ها

صفحه اصلی / دوازدهمین كنفرانس بين المللی مهندسی صنايع و سيستم ها

Identifying the Challenges of Implementing Artificial Intelligence in the Construction Project Management

نویسندگان :

Arian Fadaie¹ Rohollah Ghasemi²

1- دانشگاه تهران 2- دانشگاه تهران

کلمات کلیدی :

Artificial Intelligence،Construction Project Management،AI Implementation Challenges،AI Application،AI Adoption،AI Challenges

چکیده :

Artificial Intelligence (AI) has emerged as a transformative technology with the potential to improve construction project management through enhanced decision-making, predictive analytics, automation, and process optimisation. Despite these benefits, the construction industry continues to face significant barriers that hinder effective AI adoption. This study aims to identify, classify, and synthesise the key challenges associated with implementing Artificial Intelligence in construction project management. A qualitative meta-synthesis approach was employed following the seven-step framework proposed by Sandelowski and Barroso. A systematic search of Scopus and Web of Science databases was conducted for studies published between 2016 and 2026. After a multi-stage screening and quality assessment process using the Critical Appraisal Skills Programme (CASP) checklist, 43 high-quality studies were selected for analysis. Through inductive coding and thematic synthesis, 18 open codes representing specific implementation challenges were extracted and organised into six main dimensions: Data, Technical and Infrastructure, Financial and Economic, Human Resources and Expertise, Cultural and Organisational, and Legal, Ethical, and Regulatory challenges. The findings indicate that data-related issues, including incomplete, fragmented, and non-standardised data, represent the most critical barriers to AI implementation, while cultural and organisational factors influence long-term adoption and acceptance. The proposed framework provides a comprehensive taxonomy of AI implementation challenges and offers construction managers, researchers, and policymakers a structured understanding of the multidimensional barriers affecting AI adoption. This study contributes to the existing body of knowledge by bridging fragmented research findings and establishing a foundation for future empirical studies and decision-support models aimed at facilitating successful AI-driven digital transformation in construction project management.