Bringing AI into Business Education: The Future of Finance

Behind wrought iron gates and iconic gothic archways, students making their way back to campus this fall may be introduced to a new type of classmate. With the rise of artificial intelligence, some Chicago Booth faculty are debating whether, and how, to invite AI into the classroom. From AI models specifically trained on course material to assignments that require the use of ChatGPT, the modern student has an entirely new set of tools at their disposal.

There is a divergence of opinions about the use of AI in class instruction, with those completely against its use, and less frequently, those embracing its use. Assistant Professor of Accounting and Applied AI and Asness Junior Faculty Fellow Bradford Levy advocates for the latter. With the launch of Chicago Booth’s new AI concentration this fall, Levy is preparing to show students how to use—and question—AI in finance. He shared how he plans to effectively incorporate the technology into his teaching as the presence of AI continues to grow. 

AI in the Classroom

When Levy was an MBA student himself at the University of Michigan, he found that the most valuable classes were often about cutting-edge topics. Putting himself his students’ shoes, he asked himself “if I was a student paying tuition, what would I want to learn today?” The question guided Levy’s decision to share his own interest in applying AI to processing financial information. 

His new class, AI and Financial Information, directly encourages students to engage with AI tools (as long as they disclose how and when they’ve been used). The required transparency comes not from a fear of cheating or misuse, but from genuine curiosity. “AI is evolving so rapidly that if a student is using it in a novel way, I want to know,” Levy explained. “We can learn interesting and valuable insights from the creative ways students approach AI.”

Levy designs assignments to be brief but thought-provoking and spark new questions. He asks: Can you trust what the model just gave you? Why did it miss this detail and how would a human approach it differently? Through collaboration, students consider how AI approaches the nuances of a given problem, and where it falls short. AI remains a new tool, but a cycle of disclosure, discussion, and iteration in this class turns scattered insights into a more synthesized understanding that students can carry forward.

To Levy, using AI is similar to using calculators or spreadsheets. “Students still have to know which numbers go where and which functions to use,” he said. “The difference with AI is that with a very simple prompt a model can spit out work the user does not fully understand.” As they note their use, Levy is able to see the specific ways students are using models so that he can refine assignments to promote responsible, effective practices.

The format of Levy’s new class was informed by his time in chemistry and physics labs as an engineering student. While one can potentially grok a reaction such as “Zn(s) + CuSO₄(aq) → Cu(s) + ZnSO₄(aq)” from their seat in a lecture hall, an even deeper understanding can be gained by actually adding zinc to a copper sulfate solution and watching the copper precipitate out before one’s eyes.

AI’s complexity is best understood the same way. In his class, hands-on experience will come from applying methods to processing large volumes of financial information using Python. “Every lab is designed to highlight how amazing AI is—and 30 seconds later, how terrible it is. Then we talk about why it failed and how to avoid that in practice,” says Levy. 

Practice and Impact

Levy also sees this class as an opportunity for collaboration. Levy’s teaching assistants (TA) are often students from the College— not AI chatbots just yet—connecting MBA and undergraduate communities. One of his undergraduate TAs, an economics major in the Trott Business Program and Financial Markets Program, partnered with a Booth student he met in Levy’s class on a business venture, a natural consequence of a classroom environment encouraging students to share ideas across varying academic backgrounds and levels of technical fluency.

With only a few prerequisites, Levy’s goal is to build a class that is a jumping-off point for anyone curious about AI’s role in finance. “I try to design a course where you don’t need a computer science degree to show up and learn something which will be useful,” he says.

Still, Levy doesn’t pretend learning is easy, or that it should be. Learning is an inherently difficult process which requires the exertion of effort, as such he’s cautious about how much AI is used in the classroom. If students rely on it too heavily, especially during the learning phase, the real takeaways might not stick. Instead of using AI tools to learn material, Levy wants students to think about them deeply, apply them responsibly, and question them at every step.

Structured Thinking, Applied

Booth has always emphasized structured thinking. Levy sees AI as an extension of that, not a disruption, as models take things that are very qualitative and convert them into numbers. This course will focus on using these models to provide inputs to the quantitative frameworks that Booth has been instituting for years. In the classroom, that can mean turning financial disclosures into structured data that a model can use, wiring a retrieval-augmented generation pipeline, or coding workflows that automatically identify abnormal expenses. With this approach, it feels almost natural for Booth to pioneer the application of AI to business education.

When we asked Levy about his hopes for the future of the AI concentration, he said, “I like to win. I want Booth to be #1.”

Levy embodies the Center for Applied AI’s mission to employ AI rigorously and responsibly and translate ideas into real-world impact. By bringing that mission into the classroom, Levy’s course grounds theory in practice and equips students to understand the potential and the pitfalls of AI so they can make informed decisions in financial markets as AI technology continues to evolve.

Explore Professor Levy’s AI & Financial Information course.