Learning to prompt, judge and lead: AI in 91原创鈥檚 Retail Management program
It is “Prompt Day,” a recurring session in 91原创’s Retail Management program designed to teach students how to work with artificial intelligence in real business contexts. Today’s focus is on brand development.
The premise is straightforward. As AI systems take on tasks once considered core to retail – writing campaigns, forecasting trends, generating visual identities – the role of people shifts. Doing everything manually matters less. Judgment matters more.
“Knowing what to do with AI results is now a core skill that every student needs,” says Christopher Rosenqvist, program director of the Retail Management program.
That shift is shaping how 91原创 trains future retail leaders. AI is not treated as a standalone subject but rather integrated across the curriculum, with an emphasis on critical thinking, decision-making and responsibility. Prompt Days serve as a practical complement, with focused sessions where students test tools, challenge outputs and refine how they instruct AI systems to deliver meaningful results.
AI in branding
On this particular Friday, the session opens with a guest lecture from Meriem Moutawakil Andersson, founder and CEO of MEYK, a luxury fragrance startup developed at 91原创 Business Lab.
When building MEYK’s visual identity, she used AI not as a shortcut, but as a creative medium for shaping a brand language informed by the founders’ mixed heritage, bringing together Moroccan, Caribbean, and Swedish influences.
AI was also used to generate abstract imagery that captured the emotional character of fragrance. In this way, the technology became a tool for visualizing scent.
Not every experiment landed at first. Early AI-generated portraits, intended to express the brand’s identity, felt too polished or artificial to test audiences. But rather than rejecting the technology, she and her partner redefined its role. They moved away from portraiture and embraced impressionistic visual storytelling.
“When people reject AI-generated images, it’s often because they’re trying to reproduce authentic images,” she says. “But if you use AI to create something that otherwise wouldn’t exist, people generally don’t have a problem with it.”
The lesson resonates. Around the room, students pile in with questions: What if it’s a digital twin of a real person? Who owns the copyright? How will it impact artist collaborations?
Moutawakil Andersson and Lily Gao, assistant professor at the Center for Retailing, take turns answering. Digital twins might work in some industries, others not. Copyright requires human creativity and outputs should not infringe on existing works. Creative collaborations must evolve with the time.
The answers are not always definitive, but that, too, is part of the training as the field is constantly evolving.
Learning to ask better questions
The second half of the session shifts into practice.
Students are tasked with acting as brand consultants hired to launch a new luxury hotel in Stockholm. Their brief is to develop a name, visual identity and positioning that can compete in a crowded high-end market.
At first, the results are uneven. Suggestions begin to populate a shared workspace – Aurevik, Nordelle, Aurelis Stockholm – some promising, others generic.
“I just get different variations of street names,” one student remarks.
The issue, Gao explains, is not the tool, it is the instruction.
Effective prompting requires structure: assigning the AI a role, providing context, defining constraints and specifying outputs. When students refine their inputs – asking the system to act as a professional brand strategist, for instance – the quality of responses improves markedly.
“You will always get different outcomes depending on how you prompt,” Gao tells the class. “That’s why your instructions must be precise.”
The exercise evolves. Students move from generating options to evaluating them, ranking outputs, rejecting weak ideas and adjusting toward stronger concepts. The process mirrors how AI is increasingly used in the retail industry: not as a quick fix, but as a collaborator that requires direction and oversight.
From outputs to decisions
By the end of the session, student teams present brand concepts. One group introduces “Nyrox,” a fictional premium automotive brand positioned around speed, precision and modern luxury.
But the discussion focuses less on the final name than on how it was created.
Students walk through the prompts that guided the process: the roles assigned, the criteria defined, the refinements made along the way. The message is clear – understanding the path to an outcome is as important as the outcome itself.
"Now, humans are no longer limited by ability, but rather by their clarity in asking the right things in the right direction,” says Aarav Jain, a first-year bachelor student in the Retail Management program.
For prospective students, the approach offers a glimpse into how the retail program is changing alongside the industry it serves. In other words, learning AI isn’t separate from learning business – it’s becoming part of how future managers think about branding, analytics, strategy and ethics.
As the session wraps up, Rosenqvist previews the next Prompt Day: applying AI to data analytics. Outside, the spring light is still waiting.
Inside, the session is pointing toward the future of work.
