This semester, we had the privilege of watching our first cohort of MS Business Analytics students at CSU Channel Islands step into a learning experience unlike anything we have attempted before. What began as a partnership between the CSUCI new MSBA program, the Small Business Development Center (SBDC), and the Economic Development Collaborative (EDC) grew into a transformative experiment in applied AI education.
Last Friday, as we celebrated the culmination of the internship, we found ourselves reflecting not on the event itself, but on the teaching and learning journey behind it, what worked, what surprised us, and what lessons we might share with colleagues who are experimenting with integrating emerging technologies into their classrooms.
The initiative, partially funded by a $10 million grant from Google.org to the National SBDC AI Initiative, placed 19 CSUCI MSBA students into intensive, hands-on roles focused on applying artificial intelligence and machine learning to real-world small business challenges.
The main goal was to develop cutting-edge AI tools that would allow our advisors to do a better job and maximize what they’re doing. By combining the academic talent here at CSUCI with the SBDC’s mission, we’ve created solutions that will scale our expertise tremendously.
We were utilizing generative AI, specifically tools that introduce students to both Retrieval Augmented Generation (RAG) and Heuristic Augmented Generation (HAG) via HeuriSight and Protobots, Generative AI tools developed by Lokesh Dani at Xopolis. While RAG is more familiar, HAG is unique. We quickly realized the incredible importance of heuristics in this work. Heuristic thinking is what makes human experts unique—it’s our special way of doing things, contrasted with the large language models that seem to know everything.
This challenge immediately resonated with our MSBA program design. When we built the degree, Professor Hua Dai and Professor Minder Chen envisioned a hands-on approach to learning. This project is a perfect match for that vision. Students weren’t just learning generative AI tools; they were asked to apply them to authentic business problems, guided by experienced SBDC consultants.
Much of the public conversation around generative AI emphasizes tools like ChatGPT or Retrieval Augmented Generation (RAG). What this project taught us, however, is that Heuristic Augmented Generation (HAG) may be even more important. Working with Lokesh Dani’s HeuriSight and ProtoBots platforms, students quickly discovered that heuristics—the intuitive, experience-driven shortcuts that human experts rely on—are often the missing piece in AI development.
This reinforced a key teaching insight: Technology alone is not enough. Without domain expertise, AI remains shallow.
The SBDC/EDC consultants were the heart of the project. They brought decades of experience across industries—finance, marketing, strategy, operations—which shaped the students’ understanding and helped them translate technical models into practical tools.
We structured the internship into an MSBA course this fall semester so that every week a 90-minute session was dedicated to the SBDC AI consultancy project. Students were simultaneously enrolled in courses on the Fundamentals of Business Analytics, Python for Business Analytics, and Databases & SQL, allowing them to apply their learning in real-time.
The most encouraging part? Students began to see themselves less as learners and more as consultants—a shift that we, as educators, work hard to cultivate but rarely see so clearly.
The biggest surprise for us was how deeply students engaged with the non-technical dimensions of the project. They realized quickly that:
- Businesses don’t ask for algorithms—they ask for solutions.
- AI is only useful when it reflects human judgment.
- Consulting requires empathy, communication, and context.
At the same time, the biggest teaching challenge was helping students develop an understanding of both what AI can do and what it cannot do. This balance—enthusiasm paired with critical thinking—is a pedagogical space we will continue to refine.
The 19 students formed 8 teams; each partnered with an SBDC consultant. The resulting AI tools were more than prototypes—they were thoughtful attempts to capture and scale human expertise through generative AI.
Each student received a certificate recognizing their work under the National SBDC AI Initiative and a $1,000 stipend. But more importantly, they left with a richer understanding of what it means to build technology responsibly and collaboratively.
If there is one takeaway we would share with colleagues, it is this: Students learn AI best when the work is grounded in human problems, not technological novelty.
This internship reminded us that emerging technologies offer us—as faculty—an extraordinary opportunity to redesign how we teach. But they also challenge us to think about where expertise resides, how it is transferred, and how we prepare students for a world in which technology evolves faster than syllabi.
This was only our first cohort. We will refine the model, strengthen our partnerships, and continue learning alongside our students. We hope that this experience encourages more faculty to explore high-touch, real-world, interdisciplinary learning experiences that blend technology with humanity.
If you would like to integrate AI, experiential learning, or community partnerships into your own courses, we are always happy to share notes, reflections, and lessons learned.
Email the authors: Minder Chen, Ray Bowman, and Maria Ballesteros-Sola.
