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Across programs, teachers are weaving AI into both course design and classroom practice. It helps generate assignments, supports students between lectures and creates new ways to interact with the course material. At the same time, faculty are clear that foundational skills remain central to students’ development.

“The dilemma is that if students feel the computer is superior in writing, solving problems and being creative, they lose confidence and don’t even try,” says Christopher Rosenqvist, Program Director for the Bachelor in Retail Management. “That’s why we have to emphasize the importance of critical thinking and doing the hard work.”

A practical aide for teachers and students

For many teachers, AI has become a practical aid in course preparation. Associate Professor Lin Lerpold, who teaches corporate social responsibility and sustainability management, uses a large language model to generate multiple-choice questions based on research articles with different perspectives. The aim is to test whether students can reflect on the literature, not just recall it.

“It’s especially useful for producing plausible wrong answers, which can be quite time consuming,” she says.

Others are experimenting with AI-powered tutoring. Katerina Hellström, assistant professor in the Department of Accounting, uses a digital agent to help students revisit earlier coursework as they move into more advanced classes. Magnus Söderlund, professor in the Department of Marketing and Strategy, has introduced AI-based video avatars (pictured here) that offer additional explanations of course modules. 

Together, these tools give students more flexibility in how they interact with the material, while allowing faculty to focus more on discussion and deeper learning.

An assistant, not a replacement

Several teachers describe AI as a useful colleague rather than a substitute for their work. Milda Tylaite, associate professor in the Department of Accounting, uses it to summarize and structure student submissions, refine lecture materials and develop exercises. It can suggest clearer ways to present ideas and highlight gaps in reasoning.

But the output, she notes, is only a starting point.

“It saves some time, but it needs to be checked for accuracy and precision,” she says.

Jesper Blomberg, an associate professor at the Department of Management and Organization, brings AI directly into the classroom. Students compare AI-generated responses with their own analysis and lecturers’ input, helping them see both the strengths and limitations of the technology.

“When we push the prompting, we could make AI do nice consultancy reports, but never what we really want students to do, which is to go beyond the mainstream interpretation into more advanced critical analysis,” Jesper Blomberg says.

Rethinking assessments

The rise of AI is also changing how students are evaluated. Professor Bo Becker at the Department of Finance says traditional take-home written assignments are no longer reliable measures of student ability.

Instead, AI may necessitate greater emphasis on in-class performance and other formats that capture students’ thinking in real time.

From top left to right: Milda Tylaite, Bo Becker, Christopher Rosenqvist; from bottom left to right: Magnus Söderlund, Katerina Hellström, Lin Lerpold.

The case for foundational skills

Despite their different approaches, faculty members agree on one point: AI cannot replace the hard work of learning.

There is concern among faculty that overreliance on AI could weaken students’ cognitive development, particularly if it is used before foundational skills are in place. To understand how a research article is built, students must first read and analyze it themselves, working through its arguments, structure and evidence.

Only then, faculty argue, can AI serve as a tool for reflection rather than a shortcut.

Preparing students for an AI-driven workplace

The push to integrate AI into teaching is also coming from the labor market. Employers increasingly expect graduates to use AI to solve practical problems, and SSE is adapting its programs accordingly.

In the Retail Management program, students take part in hands-on workshops, or “Prompt Days,” where they learn to use AI tools to analyze data, automate tasks and tackle real business challenges. The aim is to pair technical skills with sound judgment, understanding both what AI can do and where it falls short.

That balance is equally relevant in other industries, where professionals still encounter errors and inconsistencies in AI output. Some faculty caution against replacing entry-level roles with AI, warning that doing so could weaken the pipeline of future senior talent.

Overall, SSE’s approach is grounded in the belief that students must first develop strong analytical foundations. Faculty stress that engaging deeply with course material – reading, interpreting and constructing arguments – remains essential.

As faculty continue to experiment, the message to students is clear: use AI to support your learning, not to do it for you.