Dr. Chris Ling is an Assistant Professor in the Marketing area at the DeGroote School of Business and the course coordinator for Commerce 1MA3 – Introduction to Marketing, a required first-year course in the Commerce program. Each year, multiple instructors teach 1MA3 across different terms using the same course content, so this change involved members of the broader 1MA3 instructional team.
For well over a decade, a group project has been a mainstay of the course. Student groups chose a Canadian public company and prepared a marketing plan that drew on everything they had learned over the semester. When it works well, the project teaches students how the entire marketing process fits together from start to finish and gives them a sense of how industry operates. In recent years, however, the Teaching Assistants (TAs) marking the project reported that submissions had become noticeably more generic, and they suspected this was in large part because students were using generative AI to write large portions of their reports. Because so much has already been written about large public companies, the assignment had become easy to hand off to AI, and it was no longer reliably producing the learning it was designed for.
After gathering feedback from the teaching team and hearing from students, the team decided the assignment needed to change to become relevant again. Instead of researching an existing company, student groups now build a marketing plan for a new product or venture of their own design. An original idea cannot simply be looked up, so the thinking has to come from the students. Groups begin by researching an unmet consumer need, brainstorm ways a new venture could address it, and select a concept. Each group submits a Concept Approval Form in Week 5, which a TA reviews and approves before the group moves on. Part 1 of the project (12% of the final grade) is a situation analysis, including a SWOT analysis, focused on the venture’s viability; Part 2 (13%) covers marketing strategy: segmentation, targeting, positioning, and the marketing mix.
The redesign also set out to teach students the value of AI when it is used in the right context. Brainstorming is a natural fit: AI can generate many options quickly and help students move past their first idea. The assignment therefore encourages students to use generative AI at the start of the project to brainstorm venture ideas (it is encouraged, not required; students are pointed to McMaster’s university-supported Microsoft Copilot, though other tools are allowed). This permitted use is set out in the course’s AI statement, which follows McMaster’s “Some Use Permitted” guideline language. However, it was important that students not simply accept the first output the AI produced. Instead, they are shown how to interact with it effectively. The assignment guidelines include the following example of low-effort versus effortful use of generative AI:
Figure 1. Example from the assignment guidelines contrasting a low-effort prompt with an effortful, iterative sequence of prompts.
As the example shows, students are expected to work with the AI iteratively to arrive at the strongest new venture idea for their group. Rather than accepting the first output, they feed in the research their group has already conducted, ask for a genuinely wide range of options, pressure-test the most promising candidates, and then judge the results themselves. The underlying message is that AI can add real value and productivity, but only when the judgment and evaluation remain with the students. The marking rubric was also revised to reflect this: brainstorming now carries marks through an Ideation and Concept Selection criterion, which is part of Part 1’s 12% and rewards a thoughtful, iterative process, not just the final idea. Using AI is not required to earn these marks: students who brainstorm without AI can still receive full marks, although instructors point out in class that generative AI can help facilitate the brainstorming process.
The guidelines also set clear guardrails on “good” and “bad” AI use. Students are told that using generative AI to produce facts, statistics, or sources is counterproductive: these tools can generate plausible but inaccurate information, and students remain responsible for verifying every fact themselves. Students are taught to cite every source in Chicago style, which makes it possible for TAs and instructors to check the facts and figures in each report. Students are also told explicitly that submitting analysis written by an AI tool as their own work constitutes academic misconduct.
Because this is the first year the new assignment is running, feedback so far is limited and has been gathered informally. Early feedback suggests that the redesign has brought new energy to a long-standing staple of the course and that the assignment is well suited to teaching marketing in an age of generative AI. Giving students explicit direction on how the course wants them to use AI – as a brainstorming partner whose output they must question, verify, and refine – appears to be helping them get more out of the project. The approach is also intended to reflect how AI is increasingly being used in industry, where the tool can speed up idea generation, but people remain accountable for the judgment calls.
For context, the TAs’ concerns about increasingly generic work under the previous assignment were also reflected in the grades. In earlier years, a few reports failed and a few stood out with an A+. In 2025-2026, the spread of grades narrowed: most grades clustered in the B to A range, with no standout A+ submissions, even through the course enrollment was larger that year due to increased university enrollment. Because the new assignment is only in its first term, it is too early to say whether it reverses this pattern; the grade distribution at the end of the year, including whether standout submissions return, will offer an early indication.
The new assignment will run in both the Fall and Winter terms of the 2026–27 academic year, across the multiple instructors and sections that teach 1MA3. The teaching team will use this first year to refine any pain points and to clarify where students need additional support from the course. Because TAs now review and approve each group’s concept, they will also need training on how to evaluate student concepts consistently. For instructors considering a similar change, a key takeaway is that shifting from an assignment students can research to one they must invent moves the critical thinking back to the students, and that showing students what good AI use looks like matters as much as telling them what is prohibited.
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Ling, C. (2026), From Analyzing to Inventing: Redesigning a Marketing Group Project for the Age of AI, Teaching in the Age of AI: Examples, From Analyzing to Inventing: Redesigning a Marketing Group Project for the Age of AI, Licensed under Creative Commons BY-NC-SA 4.0.
Teaching in the Age of AI