Modeling the Barriers to Implementing Artificial Intelligence in Desalination Supply Chain Using MICMAC(مقاله علمی وزارت علوم)
حوزههای تخصصی:
This study examined the barriers to adopting Artificial Intelligence (AI) in desalination supply chain (SC), a sector increasingly seen as vital for tackling global water scarcity. Despite AI’s proven ability to improve efficiency, sustainability, and decision-making in complex supply chains, its implementation in desalination systems encounters formidable challenges. Through a comprehensive literature review and expert consultations, sixteen barriers were identified and analyzed structurally using the MICMAC approach. The results showed that four factors are the most influential barriers and serve as bottlenecks for successful AI adoption: lack of funding and capital, lack of standardization and interoperability, shortage of specific skills and talent, and data privacy and security concerns. The present study emphasizes the need for integrated strategies that include financial support, common standards, skill development programs, and strong data protection frameworks. It also highlights the importance of collaboration among governments, private sector stakeholders, and research institutions to overcome systemic obstacles. The findings may not only offer insights into the key drivers of AI implementation in desalination but also provide a roadmap for policymakers and industry leaders aiming to develop more resilient and sustainable water management systems.