Multi-Criteria Decision-Making Model for Rank Strategy to Overcome Barriers to Integrating the AI and Cloud Systems in the IT Industry

Abstract

This study proposed a decision-making framework for identifying key barriers when implementing Artificial Intelligence (AI) and cloud systems in the Information Technology (IT) industry. Then, it proposed a set of strategies to overcome these barriers. We proposed a Multi-Criteria Decision-Making (MCDM) methodology for various criteria. Multiple barriers, such as cost, technology, environment, and digitization, should be analyzed. The Evaluation Based on Distance from Average Solution (EDAS) method is an MCDM method logy used to rank the alternatives. The criteria weights are computed by the average method. This study used ten barriers and ten strategies. The results show that technological barriers have the highest importance in this study. The sensitivity analysis is conducted to show the stability rank of alternatives. There are eleven cases in which criteria weights are proposed. Then, the EDAS method is used to rank the other options. The results show the stability of the rank under different cases.