Abstract

The impact of generative AI across economic sectors is still emerging; however, workforce disruption attributed to AI adoption is already becoming visible. Recent reports indicate that organizations are increasingly associating layoffs with AI implementation initiatives. For example, CBS News reported that 26% of April 2026 job cuts were linked to AI-related organizational changes (CBS, 2026). This perception of AI as a replacement technology is also influencing higher education, where some instructors view AI as a potential threat to the teaching profession itself. Consequently, educational institutions are struggling to determine how to respond to the rapid adoption of generative AI technologies. Opinions regarding AI in education remain divided. Some educators view AI primarily as a threat that lowers barriers to academic dishonesty by enabling students to generate reports, solve problems, and complete assignments with minimal effort. Others view AI as a transformative opportunity capable of enhancing learning through personalized tutoring, adaptive explanations, and immediate feedback tailored to individual students’ needs and learning styles. Information Systems (IS) educators face additional pressure because AI itself is a core topic within the discipline. Students increasingly expect IS faculty to make informed and effective decisions regarding AI integration while also providing educational experiences enhanced by these technologies. Consequently, instructors face increasing tension between preventing misuse and leveraging AI to improve learning outcomes. These concerns directly influence course design, instructional delivery, assessment strategies, and student engagement practices. This TREO talk aims to encourage IS instructors to share practical experiences implementing AI across different stages of the educational process. Because many examples already exist of the use of AI and, more specifically, Generative AI in classes, assessments, tutoring, simulations, etc., the emphasis is on the risks, mitigation strategies, and educational benefits associated with AI adoption in the classroom through practical, tested implementations. Several examples of AI implementation in IS education are presented alongside preliminary observations regarding their opportunities and challenges to initiate the discussion. The goal is to develop a framework through which AI-based educational innovations can be qualitatively and quantitatively evaluated according to their risks and pedagogical value. The timeliness, relevance, and urgency of the topic, combined with the session’s practical focus, create a strong opportunity for meaningful discussion that can evolve into future collaborations and additional academic outcomes.

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