Carlson Students Balance AI Fluency and Foundational Rigor

Minnesota Carlson’s approach to artificial intelligence is simple: it’s both essential and insufficient.

There is no question that our students will need to leverage AI tools in their careers. Businesses in every corner of the economy are building out new processes and looking for ways to gain a competitive edge. Using these tools is an everyday expectation in most professional jobs. However, AI can’t solve novel problems; that requires human ingenuity.

Navigating the AI Shift

“Employers increasingly assume some level of AI familiarity, and expectations for ‘entry-level’ work are changing as AI becomes part of everyday professional practice,” said Meghan Stiling, Carlson’s AI in Teaching Innovation Fellow. “At the same time, the skills that remain most differentiated are deeply human: judgment, communication, critical thinking, synthesis, and decision-making.”

Stiling, a lecturer in the Undergraduate Program, has been working to understand the current state of AI in the Carlson classroom, the skills our students will need to succeed, and build a structured, scalable AI capability across teaching and learning. 

In addition to engaging with faculty and students about their current uses of artificial intelligence and the questions they still have, Stiling has been experimenting with the technology in the courses she teaches: Impact Lab Problem Solving and Impact Lab in Action.

In the classroom, AI isn’t just a tool; it’s a thinking partner. Students are using Google's 'NotebookLM' to build custom environments for their course materials allowing them to easily return to topics from previous semesters and leverage their knowledge. They use AI to stress-test their brainstorming and uncover blind spots. Students learn to collaborate with AI, then verify and challenge AI-generated information, always watching for biases and inaccuracies.

Fundamentals First

In a world with a calculator in every pocket, mental math is still important. That ability to make a quick estimate makes it possible to understand when the calculator gives the wrong answer. The same is true when working with AI - students will only be able to catch inaccuracies and hallucinations if they already have a good understanding of the underlying questions and processes.

That’s why our curriculum remains committed to rigorous business fundamentals. Every instructor is considering the appropriate role of AI in their course, and sometimes that means strictly limiting its use.  We want to ensure students achieve mastery of core business concepts—the 'how' and 'why' of decision-making—before applying AI as a tool to accelerate or scale their work.

Preparing Students to Lead

As AI reshapes the professional landscape, Carlson’s long-standing commitment to experiential learning continues. In a future where machine labor can increasingly handle routine analysis and data processing, skills like critical thinking and creative problem-solving will define the next generation of business leaders. Our signature experiences, such as the Impact Lab, serve as the ideal training ground for this new environment. By tackling real-world, ambiguous challenges in partnership with the local business community, students aren't just learning to use AI; they are learning how to lead with it. This hands-on approach ensures our graduates possess not just technical proficiency, but the critical, collaborative, and ethical instincts to use technology as a catalyst for meaningful change. 

The University provides access to Google Gemini for all students, ensuring that they are able to become proficient with the same tools that future employers will be expecting them to use.

The results are already paying off: students returning from internships report that their 'AI-native' insights allowed them to drive real efficiency and process improvements. Major employers tell us they are continuing to grow their teams, adjusting for this new technology. They’re widening job descriptions and looking for creative thinkers who can successfully collaborate with machine labor. 

Stiling’s work as our AI in Teaching Innovation Fellow will continue into the 2026-27 academic year. She’ll be building a more structured, scalable approach to AI in teaching—one that prioritizes student agency, faculty enablement and continuous feedback. Ultimately, Carlson will continue to do what we do best: grow future leaders who can confidently navigate the business world, leveraging the technology available to them while maintaining essential foundational knowledge and decision-making skills.