MODELING THE CRITICAL SUCCESS FACTORS FOR EMPLOYING AI IN BUSINESS DEVELOPMENT: A M-TISM APPROACH

Abstract

The integration of Artificial Intelligence (AI) in business development is rapidly transforming organizational strategies, enhancing decision-making, and fostering innovation. However, the successful implementation of AI requires a deep understanding of the critical success factors (CSFs) that influence its effectiveness. This paper employs a Modified Total Interpretive Structural Modeling (M-TISM) approach to identify, model, and analyze the key CSFs for employing AI in business development. Through a systematic literature review and expert input, the study uncovers a set of interconnected factors such as technological infrastructure, leadership commitment, organizational culture, data management, and employee readiness. The M-TISM framework helps in illustrating the hierarchical relationships and interdependencies among these factors, offering a comprehensive understanding of the complex dynamics involved in AI adoption. The findings provide valuable insights for business leaders and decision-makers, offering strategic guidance on how to align organizational resources, culture, and processes for successful AI integration, thereby driving sustainable growth and competitive advantage in business development.