This course explores how higher education institutions can design and scale student workforce development programs using artificial intelligence as a structured support system for learning, mentorship, and operational contribution while also supporting the day-to-day needs of operational staff. The presentation demonstrates how students can be integrated into live University operations while developing workforce ready technical and professional skills.
Participants will learn how students support real institutional work through operational tasks, structured workflows, documentation, and program support within clearly defined roles and guardrails. The session highlights how AI can be used to scaffold learning, standardize workflows, support reflection, and scale coaching without replacing human judgment or increasing institutional risk. While focused on cybersecurity, the model is positioned as transferable across student workforce programs.

Learning Objectives:
1. Understand how to design an AI supported student workforce development model that integrates students into live operational environments while maintaining institutional trust and oversight.
2. Identify how artificial intelligence can be applied to scale coaching, documentation, and skill development within student programs without replacing human mentorship.
3. Examine key structures, roles, and guardrails required to manage risk and ensure quality in AI supported student led operations.
4. Apply a transferable framework for positioning student workforce programs as strategic assets that support career readiness and institutional outcomes.