Many business school graduates struggle with practical workplace skills such as negotiating, finding mentors, and responding to microaggressions. At the University of Guelph´s Lang School of Business and Economics the new course Launching Future You – Strategies for Career Success addresses that gap by combining interdisciplinary teaching with technology. The course is open to students across the university and emphasizes transferable skills, resilience, and lifelong learning while leveraging generative Artificial Intelligence to create realistic practice opportunities.
The core pedagogical innovation is two custom simulations, built by Ametros Learning and set in a fictional firm called Green Thumb. In one simulation students engage a mentor, handle manager check-ins and write emails; in the other they practice allyship when a coworker faces discrimination. Interactions happen through chat and email interfaces that mimic real workplace tools. Because each simulation is trained on specific course materials, conversations diverge for every student and the system can give immediate, tailored feedback. That design supports scalability for large cohorts and reduces the incentive to outsource answers to other chatbots since no external tool has the same course-specific training.
Assessment combines formative and summative elements. Students complete about five graded interactions per simulation, with criteria such as professionalism and empathy translating into numerical scores. The simulations return instant comments like ´You were right to suggest this approach in your meeting with Deepti´ and point totals for each exchange. The grading method forces application of taught concepts; as the instructor notes, ´You can have a good interaction in the simulation that scores a 0 if it does not demonstrate application of content from the course module.´ Some students have pushed back when unfamiliarity with course material produces low scores, and the instructor has established a streamlined appeals process and a feedback loop with the vendor to correct discrepancies.
Despite measurable benefits, the rollout surfaces broader questions about data privacy, algorithmic bias, and academic integrity. The article argues that generative Artificial Intelligence should be treated as an extension of teaching capacity rather than a replacement for human instruction. With ethical guardrails, simulation-driven learning can deliver faster feedback, equitable access at scale, and practical exposure to the kinds of AI-driven assessments students will encounter in the modern job market. The recommendation is clear: embrace the opportunities of Artificial Intelligence thoughtfully, and prepare students to collaborate with these tools wisely.
