How can we improve AI competencies for tomorrow's leaders: Insights from multi-stakeholders’ interaction

Abstract

This study investigates factors influencing artificial intelligence (AI) competencies in higher education for sustainable development using learning theories. Utilizing a mixed-method approach, it analyzes responses from 525 students and interviews with 35 faculty members from five Indian universities. The study employs confirmatory factor analysis (CFA) and structural equation modeling (CB-SEM) to explore relationships between various learning approaches and AI competencies. Findings indicate that collaborative learning, problem-solving, and cognitive competence significantly contribute to AI proficiency. Human-tool collaboration and self-learning also enhance students' understanding of AI concepts, fostering strategic decision-making in business contexts. Additionally, thematic analysis from qualitative interviews identifies critical themes for developing an AI curriculum framework, including curriculum design, pedagogical strategies, ethical considerations, and global perspectives. The research provides an integrated theoretical model and offers practical recommendations for enhancing AI education, emphasizing the importance of interdisciplinary collaboration and ethical AI usage in management education.