Pathways to AI-Ready Entry-Level Talent for Industry Domains: Modular, Adaptive Design Principles for Business-School Curriculum
In Plain Terms
Generative AI is automating exactly the entry-level tasks that new graduates used to learn on — breaking the traditional apprenticeship path into skilled work. This paper lays out design principles for business-school AI curricula that adapt as job skills shift: students progress from no-code tools to full coding, course content is continuously realigned with employer demand signals, and a hub-and-spoke model spreads the program across institutions. The design is running in practice as the AIX Hub, with over 1,000 students and 11 industry partners in its first deployment.
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APA Rai, A., Ramesh, B., Breazeal, C., Klopfer, E., Ampel, B. M., George, A., Fu, X., & Kota, M. (2026). Pathways to AI-Ready Entry-Level Talent for Industry Domains: Modular, Adaptive Design Principles for Business-School Curriculum. In Proceedings of the International Conference on Information Systems (ICIS).
BibTeX
@inproceedings{rai2026pathways,
title={Pathways to AI-Ready Entry-Level Talent for Industry Domains: Modular, Adaptive Design Principles for Business-School Curriculum},
author={Arun Rai and Balasubramaniam Ramesh and Cynthia Breazeal and Eric Klopfer and Benjamin M. Ampel and Amrita George and Xinyu Fu and Madhu Kota},
booktitle={Proceedings of the International Conference on Information Systems (ICIS)},
year={2026}
}
Benjamin M. Ampel
Assistant Professor in Computer Information Systems and Director, Center for CyberAI Research (CCAIR)
My research focuses on AI-enabled Cybersecurity, including Cyber Threat Intelligence, Large Language Models, and Phishing Detection.