Abstract: As artificial intelligence (AI) becomes one of the most important driving forces in industrial innovations, more business schools, mostly in graduate programs, are introducing AI in their curricula, particularly in information systems (IS) curricula. However, there appears to be a paucity of research on the AI curriculum. This study examines the current status of the AI curriculum in both undergraduate and graduate business schools and provides recommendations for future AI curriculum development. The study develops a technical competency model for AI curriculum based on both MSIS2016 - Global Competency Model for Graduate Degree Programs in Information Systems and IS2020 - A Competency Model for Undergraduate Programs in Information Systems and the AI technical competencies. Using text mining analysis, we collected and analyzed AI courses from the top 46 business schools at both undergraduate and graduate levels, ranked by US News in 2020. The findings indicate that machine learning is at the core of the AI curriculum in business, and most AI curricula are a hybrid of AI and data analytics. This acknowledges that the AI curriculum is still at its early stage, and business schools are closely adhering to the industrial development trend. The proposed technical competency model for AI curriculum can serve as a guideline for future AI curriculum development in business schools. We hope this study provides systematic insight into AI curriculum and offers recommendations for business education, in IS programs specifically.

Keywords: Artificial intelligence, Business analytics, Data analytics, Machine learning, Deep learning, Text mining

Download This Article: JISE2022v33n4pp416-426.pdf

Recommended Citation: Chen, L. (2022). Current and Future Artificial Intelligence (AI) Curriculum in Business School: A Text Mining Analysis. Journal of Information Systems Education, 33(4), 416-426.