Piecing Together the AI Puzzle

Artificial intelligence is dramatically changing the business landscape and business education with it. As the technology’s future evolves, the complete picture remains unclear. However, pieces of this complex puzzle are taking shape at Minnesota Carlson.

Google’s generative AI tool, Gemini, is now available for use at the University of Minnesota. However, more innovation is underway. People across the Carlson community are crafting solutions to harness AI’s power in a responsible, ethical, well-grounded manner—from faculty shaping the academic strategy, to the IT team creating the technological infrastructure, to students dreaming up new applications. In an atmosphere ripe for experimentation, Minnesota Carlson is diving into what it means to create transformative business education for the workforce of tomorrow.

Time-Tested Methods for Tomorrow’s Tools

Workforce preparation is top of mind as faculty members integrate AI into the school’s curricula. Associate Dean of Academic Innovation & Operations Vlad Griskevicius offers a perspective that slices through hype to focus on a fundamental question: In a world where AI can produce marketing plans, financial analyses, and business strategies at the click of a button, what value do human graduates provide?

He predicts a near future where employers routinely test job candidates by asking them to evaluate AI-generated work. The candidates who respond with “It’s pretty good already” won’t get hired. The ones who can identify assumptions, spot weaknesses, and suggest improvements will thrive.

“If you’re an employer under financial pressure to increase productivity, you don’t need another human who can do the same thing AI can already do for you at a much cheaper cost,” Griskevicius says. “The solution isn’t to teach students to compete with AI—it’s to prepare them to work with it in ways that create unique value.”

That vision drives three strategic priorities for shaping AI education at Carlson. First is doubling down on disciplinary expertise. “There’s an issue if you don’t understand marketing; you can show me all your fancy gadgets and widgets, but I can get AI to do it for me,” he notes, adding that graduates need deep foundational knowledge to evaluate and improve AI outputs.

The second priority is expanding experiential learning. Entry-level roles that traditionally provided workplace training are disappearing as AI automates those functions. Griskevicius says graduates must be job-ready with real-world problem-solving experience—precisely what classes and programs, like the Impact Lab and the Carlson Analytics Lab, provide.

Third is integrating AI as a daily practice rather than a technical specialty. Griskevicius draws parallels to how business schools approached internet adoption in the late 1990s. Initially, they created “Internet 101” courses, but those quickly disappeared as internet use became intuitive. “AI will be similarly easy to use,” he says, with integration happening within Carlson’s existing disciplines rather than through standalone programs.

Infrastructure for Safe Innovation

While Griskevicius and the faculty focus on preparing students for AI-driven careers, the school’s IT team is tasked with another piece of the puzzle—how to build a foundation that enables such innovation. It’s a challenge that starts with protecting privacy and safeguarding against security risks. “Student data is federally protected,” says Carlson Cloud & AI Architect Brad Kaufman, ’19 MSBA. “We also need to ensure that data is protected according to the University’s policies. So one of our main tasks is to make sure information doesn’t end up someplace it isn’t supposed to go.”

Led by Carlson IT Director Connie Buechele, ’13 MBA, the team has embraced an approach that gives students a range of AI tools while also maintaining strict data protection. Case in point: They’ve developed a TA bot, which is an AI assistant that provides 24/7 support on select course topics. Pilot access was limited to students in participating sections via the University’s learning management system. “The way you deploy and manage a TA bot is different from how you’d handle general-purpose, ChatGPT-type assistants,” says Kaufman. “We do a lot of fine-tuning behind the scenes with the TA bot to safeguard privacy and make adjustments to give students the optimal experience.”

The IT team has several other projects either in operation or in the works. One that’s already in place is a tool that helps students write computer code. “The students aren’t necessarily using it just for the sake of writing code,” Buechele says. “A good use case example would be someone in an analytics course. They can use AI to help write the initial code, so they can spend more time on the analytics rather than the coding.”

One project still in the development stage is a platform that will let faculty, staff, and students create their own specialized AI assistants for different purposes—research, student support, recruiting, and more. A longer-term goal is to extend these into capabilities where multiple AI systems—or agents—can coordinate and build on each other’s outputs. That opens the door to flexible “AI teams” with different strengths, as Kaufman notes.

And, in line with Griskevicius’ vision for Carlson’s curricula, all of the IT team’s innovations aim to support students as they enter the workforce. “Employers want graduates with practical AI tool experience and knowledge,” says Associate Director of IT Mark Hove. “That sort of workforce preparation is at the heart of everything we do.”

Innovation From Student Insight

As Carlson’s faculty and staff continue to build up the school’s AI applications, some students are inspired to tackle the AI puzzle on their own terms. Gurasis Singh, a senior in the Undergraduate Program double-majoring in Entrepreneurial Management and Political Science, is one such student. Up until recently, he never imagined himself as an AI company founder. That changed when he took the yearlong Entrepreneurship in Action course through Carlson’s Gary S. Holmes Center for Entrepreneurship, during which students create an idea for a start-up and launch the business.

Singh, with classmates Isaac Porter and Samra Bojcic, created Echo Learn, an AI platform that reimagines how AI technology can enhance rather than undermine student learning. The idea grew out of Singh’s interest in education policy, sparked by his political science courses. More specifically, he focused on active learning and different learning styles, including discussion, practice, and learning by teaching—a technique that can boost retention rates by as much as 90%. But after Singh conducted more than 50 interviews with professionals across the education industry, he zeroed in on a common challenge: Time and resource constraints simply don’t allow for active learning. On top of that, the rise of AI has made it all too easy for students to rely on the technology to do their work for them, something Singh calls an “education-tech misalignment.”

This research led to the creation of Echo Learn. The idea is elegantly simple: Students upload course materials—textbooks, case studies, articles—and then engage in conversation with an AI chatbot that asks questions rather than providing solutions. Students must explain concepts to it, defend their reasoning, and demonstrate comprehension before the system acknowledges mastery. The system also won’t give answers—it demands them, which helps avoid the misalignment issue.

The work has gained attention. Echo Learn was awarded the Most Innovative prize at the Holmes Center’s annual Biz Pitch competition and has been piloted in some Carlson classes. While the platform is already live at Echolearn.org, Singh says he and his team are still making improvements, taking steps to create a positive social impact in education. “We don’t have all the bells and whistles yet,” he notes. “We’re testing it, working on second-stage development, and figuring out our go-to-market strategy to help as many instructors and students as possible.”

Building the Future

As AI technology continues to develop and change, Carlson faculty and staff are determined to change with it—empowering students to do the same.

No one claims to have all the answers. As Singh says, he’s still fine-tuning his product and exploring what’s possible. Meanwhile, Carlson’s IT team is building secure infrastructure while learning what works, and faculty are preparing students for a reality where AI amplifies human expertise even as that reality continues to evolve.

Put together, these efforts at Carlson show that solving the AI puzzle isn’t about having perfect solutions now, but about thoughtful experimentation with an eye on a rapidly shifting future.

Illustrations by Blake Cale