Bridging the Industry-University AI Competency Gap: A Mode 2 Approach to GAI-Integrated Education

The rapid adoption of Generative Artificial Intelligence (GAI) is transforming Information Systems (IS) education, yet university curricula remain misaligned with industry expectations. This study investigates the industry-university AI competency gap, examining how Mode 2 knowledge production can facilitate GAI-integrated curriculum innovation. Conducted within a Master of Business Analytics course, this research employed a qualitative approach, using structured focus groups with industry professionals to identify essential GAI-related competencies, pedagogical approaches, and assessment models and co-create an assessment. Content analysis of focus group findings highlights the need for process-oriented assessments, GAI literacy training, and iterative industry collaboration to ensure graduates develop critical validation, ethical reasoning, and analytical oversight in GAI-assisted decision-making. Theoretically, this study extends Mode 2 knowledge production by demonstrating its relevance in curriculum co-creation for AI-integrated education. It offers practical recommendations for universities, educators, and policymakers, advocating for sustained university-industry engagement to embed problem-driven, industry-relevant AI competencies in IS education.