Exploring the future of agriculture using AI-enhanced research
The Department of Agricultural and Applied Economics is integrating undergraduate research and AI to address challenges in agricultural and applied economics.
As artificial intelligence (AI) increasingly shapes industries and how we work, Virginia Tech looks at how we can utilize this technology to improve research and education. As part of this effort, the Department of Agricultural and Applied Economics is experimenting with integrating AI to enhance students' understanding of real-world challenges in agriculture and applied economics.
Hannah Kwan ’25, a recent graduate with a double major in animal science and agribusiness, explored AI’s potential through a unique research project during the spring semester. This opportunity, guided by George Davis, interim department head and professor, along with Greg Estep ’83, alumnus and advisor in the food and agriculture industry, allowed her to gain greater insights into advantages and disadvantages of using AI to answer real world problems.
"I wanted to know more about how AI could help us learn, rather than being dismissed as a shortcut," Kwan said. "AI can break complex topics down and explain them in ways that are easier to understand. It’s not about bypassing the learning process but enhancing it."
"Students are going to be using AI in their careers, so we must teach them how to use it effectively and critically,” Davis said. “AI is just a tool. Like any tool, one must know how to use it. One cannot just give AI a prompt and expect to get accurate and useful answers. Prompt revisions must be supplemented and guided by their own disciplinary and background knowledge. This project is designed to simulate real-world scenarios where quick, accurate, guided, and informed research is vital to decision-making.”
The project posed three research questions to Kwan:
- What is the risk of the weight loss drug, GLP-1, for Chick-Fil-A?
- How tariffs affect the veterinary industry?
- How do owner feeding habits influence obesity in cats?
To address these questions, Kwan utilized AI to gather, refine, and integrate information to develop coherent and insightful answers.
The experiential learning project involved Kwan acting as an employee, while Estep took on the role of CEO. This dynamic simulated a professional work environment, with weekly meetings challenging Kwan to develop key insights and make critical business decisions based on her AI research.
"I always conduct research manually, but AI introduced a level of structure and speed that I had never experienced," Kwan said. "It was much easier to find relevant sources, and it helped me identify what I needed faster."
While impressed with AI’s capabilities, Kwan acknowledged its limitations. "AI is an incredible tool, but it’s not perfect. It still requires human interaction to ensure accuracy," she said.
“AI is going to revolutionize industries, including those in agriculture and applied economics,” Estep said. “I was proud to be part of this project and hope we can do more to ensure students understand not only the capabilities of AI but also the responsibility of using it wisely in real-world applications.”
Looking forward, Kwan plans to incorporate AI into her veterinary career, especially in areas such as clinic operations and business strategy. While she doesn’t foresee AI offering medical advice in this industry, she believes it could be a game-changer in areas like pricing strategies, marketing, and clinic management.
"AI could provide valuable insights to help with business decisions, from optimizing pricing to streamlining marketing efforts," Kwan said. "Its potential to enhance business operations in veterinary clinics is huge."
Kwan’s experience exemplifies the possibilities that AI presents not only in research and education but also in the broader scope of industry.