Enablers Driving Success of Artificial Intelligence in Business Performance: A TISM-MICMAC Approach
Vijay Kumar Sharma, Harish Kumar
Abstract
Organizations have recently seen a significant transition from implementing technologies in business processes. The cutting-edge technology, such as artificial intelligence (AI), makes business firms more competitive in a dynamic world. This study aims to investigate key variables that drive success of AI to improve financial performance and values of a firm. The inter-relationships among variables are established to explain the emergence of AI in a novel hierarchical model. The study deployed “Total Interpretive Structural Modeling” and “Cross-Impact Matrix Multiplication Applied to Classification” for developing a hierarchical model to analyze inter-relationships among identified key variables. The results hold important insights for strategic decisions and are useful for business firms to invest in advanced technology, such as AI, to enhance business performance and revenue in domestic as well as in global markets. Insights drawn from analysis will help business firms to grow in a competitive landscape. The decision makers can utilize the proposed hierarchical model to enhance the performance of business along with process automation. The found interactions among the key variables can be utilized to understand the ecosystem that drives business performance.