Establishing the fuzzy integrated hybrid MCDM framework to identify the key barriers to implementing artificial intelligence-enabled sustainable cloud system in an IT industry

The purpose of this research is to identify the important barriers for developing a long-term Artificial Intelligence (AI) cloud system in an Information Technology (IT) business. A fuzzy integrated hybrid Multi-Criteria Decision Making (MCDM) model was established and applied to achieve this goal. In this ongoing analysis, Delphi was used to filter the most crucial ones from a list of 18 identified parameters, whereas, Analytic Hierarchy Process (AHP) was used to assess the relevance of each parameter. Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) were further applied to identify the cause-effect relationship and to construct the hierarchical interrelationships among the parameters. Finally, to identify the driving and dependence parameters, Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) approach was used. The findings revealed that the most crucial elements in building a sustainable AI cloud system were technological, financial, and environmental concerns. More particularly, from all perspectives, digitalization is deemed to be the most critical within the group, with the greatest priority degree and significant driving as well as dependent tendency. According to ISM and MICMAC, user tendency to learn and R&D sector collaboration seems to be the most dependent and the independent factors respectively among the group. Remaining of the 13 factors are interrelated and operates as linkage obstacles. This study provides useful insights for IT firms trying to implement sustainable AI cloud systems and underlines the importance of including environmental and economic concerns into decision-making processes.