How AI Is Changing Finance: a Q&A with Yun Zhu, Ph.D.

As part of our “AI in the Classroom” series with The Peter J. Tobin College of Business at St. John’s University, we sat down with Yun Zhu, Ph.D., Associate Professor of Finance, to discuss what AI means for students entering the finance field and how his classroom is already reflecting that shift.

Why AI Is Reshaping Finance

Why is AI fluency becoming essential for students entering finance and business careers right now?  

AI has become a global force, reshaping the intellectual landscape and the job market. We are witnessing a shift in which adaptability to AI tools is no longer optional for graduates, but a prerequisite.  

The urgency to formally integrate AI into my teaching arose from observing student behavior. Since 2023, students have been using generative AI regardless of policy. Sometimes they use it effectively for information gathering, but often they use it irresponsibly by simply copying output without critical engagement. I realized we needed to pivot from prohibition to guidance. Receiving the Tobin Teaching Grant in AI Innovation this fall was the catalyst that allowed me to solidify my intention. 

My goal is to move students away from passive copying and toward using AI as a powerful engine for critical thinking and analysis in my undergraduate Fintech course.  

Connecting AI Research to the Classroom

What research are you working on, and how does it connect to what is happening in the industry?  

My latest project marks a shift from using AI solely as a research method to studying AI as a primary subject of inquiry. The most significant barrier for researchers in this space has been the lack of structured data, so our project uses a creative approach to extract AI-related research from decades-old patent data.  

Specifically, we are investigating how various dimensions of organizational capital shape a firm’s ability to generate and sustain AI-related research and development outputs. This includes looking at managerial style, corporate governance structure, human capital composition, and collaborative networks.  

Historically, AI initiatives were viewed as long-horizon, high-risk investments with uncertain returns. This made it difficult to predict success based solely on financial constraints or research-and-development spending. Our research challenges this by translating intangible organizational design into measurable predictors of AI innovation—and these are exactly the kinds of questions I bring into the classroom.  

In my entry-level Fintech course, I introduce students to the same questions I explore in my research. This brings them into the academic domain of researchers rather than keeping them as passive recipients of textbook theory.  

The integration of AI tools allows us to accelerate the heavy lifting of research—data collection, literature scanning, and statistical compilation—so we can spend class time on higher-level cognitive tasks. By using AI to handle information retrieval efficiently, students save a tremendous amount of time. They can instead focus on interpreting data, forming evidence-based opinions, and making constructive financial decisions. This mirrors the professional workflow they will face after graduation.  

Preparing Students for an AI-Driven Business World

What does a Tobin business education look like in an AI-driven world?  

Tobin is not merely reacting to trends, but is proactively building an infrastructure for the future. We have already employed several dedicated AI tools and platforms for instructors and students to explore the possibilities of this technology. The AI Innovation Teaching Grant is a prime example of this commitment, but it is part of a larger ecosystem.  

We are currently seeing a concerted effort to explore how AI affects learning across the College. For instance, the Economics and Finance department is in the process of hiring new faculty specifically aimed at bringing more AI-related coursework and material to our students. 

Furthermore, Tobin is revisiting its business core curriculum and its approach to assessment, ideally bringing AI into the picture. This holistic approach signals that Tobin is preparing students not just to use current tools, but to understand the underlying mechanics of an AI-driven economy.  

How do you see AI continuing to shape your field over the next five years, and how should today’s students prepare now?  

We are at the very beginning of a new era, and AI is evolving so rapidly that predicting its exact trajectory five years out is difficult. However, one thing is certain: avoidance is not a strategy.  

For the field of finance, I foresee AI continuing to lower the barrier to complex data analysis, making high-level financial modeling accessible to more professionals. Consequently, the competitive advantage for students will no longer be just quantitative financial modeling—it will be the ability to ask the right questions and interpret AI-generated insights strategically. We must embrace these tools in every possible way, just as we switched from financial calculators to Excel decades ago. The professionals who thrive will be those who view AI not as a replacement for human intellect, but as an essential partner in navigating an increasingly complex global market.