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AI Student Fellows support AI projects across Elon Business

消消犯 worked with faculty on classroom workshops, course resources and plans for deeper AI integration.

AI Student Fellows in the Martha and Spencer Love School of Business spent the spring 2026 semester working with faculty on projects ranging from first-year AI workshops to resources for more advanced AI use in business courses.

The program paired 消消犯 students with faculty members to support AI-related projects across the school. Student fellows helped develop and deliver workshops, interview faculty and build materials for future courses and boot camps.

Sakura Kawakami 26 worked with Scott Oakes, assistant 消消犯 professor of management, and fellow students Julia Amodeo 26 and Katie Geraghty 26 on workshops for Gateway classes.

The team visited eight classes and reached approximately 240 students through 20-minute sessions with hands-on exercises. The workshops introduced students to Gemini Pro, available through Elon, and focused on practical skills such as improving prompts through iteration and added context.

The primary goal was to establish a baseline of AI fluency among Gateway students, who are primarily first-year business students, Oakes said. We also wanted to test whether a short, bootcamp-style training session could effectively introduce students to practical AI skills within a classroom setting.

Sakura Kawakami stands near Sato Commons wearing Elon graduation regalia, with a Japanese flag displayed behind her.
Sakura Kawakami 26 helped develop and deliver Gateway AI workshops for first-year business students as part of the AI Student Fellows program.

Faculty established the projects overall objectives before the students joined. Kawakami, Amodeo and Geraghty then helped develop classroom activities, learning objectives, presentation materials, pre- and post-session surveys, and the rollout plan. The students also led the workshops and helped analyze the resulting data.

My role as an AI Fellow was to act as a bridge between students and faculty, advising students on how to use AI to enhance their learning, not replace it, said Kawakami, a Business Analytics and Project Management major from Rotorua, New Zealand. The goal was to make sure students felt confident using these tools in ways that supported them.

One focus was helping students understand that effective use of AI often requires refining a prompt rather than accepting the first response.

One of our biggest 消消犯 points was the importance of iteration when prompting AI, Kawakami said. By refining and tailoring your prompts to your own needs, you get far more accurate and useful responses.

Oakes said the student fellows strengthened the project by bringing their own experiences with AI into the classroom.

Peer-to-peer learning is incredibly powerful, he said. First-year students often feel more comfortable asking questions and exploring new technologies when they see successful upper-level students demonstrating how they actually use those tools.

Another team worked with Kem Zhang, associate professor of business analytics, on projects designed to support more advanced AI use in business courses.

Thomas Case 26, a supply chain management and business analytics major from Atlanta, G.A. and Oliver Lorraine 27, a project management and business analytics major from Red Bank, N.J. gathered input from faculty and developed materials for future workshops. One project focused on Associate Professor David Jiangs, Bring the Venture to Life entrepreneurship course, where students develop and launch venture ideas.

Thomas Case smiles for a headshot in a dark suit jacket, white shirt and patterned tie against a blue background.
Thomas Case 26 worked with Kem Zhang and fellow AI Student Fellows to gather faculty input and develop materials for future AI workshops and course support.

Based on the needs identified for the course, the team created materials for an AI-powered entrepreneurship workshop covering topics such as prompting for code, e-commerce, payment integration and deployment.

Case led the workshop design and drafted presentation materials. Lorraine documented the development process and built reusable coding templates for future workshops and boot camps.

The transition from AI users to AI builders or AI architects is an important distinction because knowing how to use a tool generally is much different than knowing how to use a tool to innovate, said Case.

Oliver Lorraine stands for a portrait wearing a light gray blazer and white shirt against a plain wall.
Oliver Lorraine 27 worked with Kem Zhang and fellow AI Student Fellows to develop materials and coding templates for future AI workshops and boot camps.

Lorraine also created Google Colab notebooks with coding templates for future use.

Zhang said the goal is to help students move beyond basic familiarity with AI tools.

For business students, knowing how to use an AI tool is expected, Zhang said. The real advantage comes when they understand how these tools can be used in problem solving and to create concrete, AI-based solutions.

Several projects from the spring semester are expected to continue during the 2026-27 academic year, including the entrepreneurship workshop, an AI Boot Camp for incoming students and additional work on AI integration.

The spring 2026 AI Student Fellows were Brandon Boudreau 27, Thomas Case 26, Oliver Lorraine 27, Dylan Stone 28, Julia Amodeo 26, Sakura Kawakami 26, Lindsay Balick 27, Katie Geraghty 26, Katrina Papierman 26 and Tristan DAdamo 28.