Teaching wisdom with AI: Students explore consumer insight through technology and reflection

For more than a decade, Professor Michael Luchs has been exploring a concept that few business school faculty address directly: wisdom. Through his research at William & Mary's Raymond A. Mason School of Business, Luchs has developed tools to measure Consumer Wisdom and has examined how individuals make thoughtful, values-driven decisions about how they spend their time, money, and energy. His work, grounded in psychology, ethics, and marketing, is guided by a deceptively simple question: What does it mean to thrive?

Luchs defines wisdom as "the art and science of thriving," a phrase that acknowledges ancient traditions while addressing modern challenges. "I've never considered myself particularly wise," he admits on his blog. "But I've always been curious—especially about human behavior and the human experience." That curiosity has led to years of research focused on the moral and psychological dimensions of consumption and their impact on personal and societal well-being. His work encourages students to engage not just as analysts or strategists, but as human beings

The convergence of wisdom and AI makes Luchs's latest course assignment especially compelling.

AI is not the answer. It's the partner.

In a recent Consumer Psychology course, Luchs introduced a novel assignment blending data analysis, personal reflection, and generative AI. Supported by a grant from the Mason School’s AI Everywhere initiative, the assignment, titled "Segmenting the Wise Consumer," challenged students to go beyond typical segmentation exercises.

While students used clustering techniques to analyze survey data and make strategic recommendations, the foundation of their analysis was Luchs’ Consumer Wisdom scale—a tool measuring how intentionally people allocate their resources and bring their personal needs and values in harmony.

Students began by completing the Consumer Wisdom self-assessment themselves—using ChatGPT to interpret their scores across six dimensions: Responsibility, Flexibility, Purpose, Sustainability, Reasoning, and Perspective. This initial exercise required students to reflect on their own consumption decisions before analyzing others’, prompting a deeper understanding of the data. They were even encouraged to engage in a real-world discussion with ChatGPT, exploring whether a specific purchase, like buying a Tesla Model 3, would be a wise choice based on their resources, lifestyle, needs, and values.

Students then worked with a broader dataset, using Julius.ai to perform k-means cluster analysis, comparing 3- and 6-cluster solutions. Each cluster reflected different consumer profiles, characterized by varying levels of Consumer Wisdom, demographics, and well-being. After exporting the results to Excel, students used ChatGPT to interpret the clusters and explore the implications for marketing strategies.

The assignment emphasized critical engagement with AI. Students were tasked not only with prompting AI for insights but also with evaluating its output. They were asked: What did AI miss? What assumptions does it make? How can you improve or clarify its interpretations for a business audience? Their final deliverable was a 500-word report advocating for one of the segmentation strategies, accompanied by a short reflection on their experience working with AI as a collaborator.

This assignment developed students’ technical skills in segmentation analysis, strategic thinking grounded in human behavior, and the critical literacy necessary to actively use generative AI tools. They gained practical experience in both the mechanics of clustering and the broader question of what it means to be an insightful, responsible analyst.

The future of business education is reflective, not just responsive.

As business schools rapidly integrate AI into curricula, there is a risk of superficial adoption—adding AI to assignments without considering its deeper implications.

Luchs’s assignment offers a thoughtful alternative: AI is embedded to enhance critical thinking, moral reflection, and personal growth.

This is not just about teaching students to use AI responsibly; it’s about helping them understand the nature of AI-generated intelligence and the human judgment required to complement it. By engaging students in critiquing AI’s interpretations and refining its outputs, the assignment fosters reflective practitioners—precisely the kind of leaders the Mason School aims to develop.

This approach also presents a model for how AI can be meaningfully integrated into business education:

• Start with purpose: What human question drives the analysis?
• Use AI to explore, not just execute: How can AI offer new perspectives or reveal gaps?
• Reclaim curation as a skill: How do we shape and refine AI’s output to align with real-world needs?
• Teach discernment, not just deployment: Can students distinguish between what is technically correct and what is wise

By framing AI use within the context of wisdom, this assignment links emerging technologies to enduring questions. It asks students: What kind of consumer, citizen, or leader do you want to be? At a time when optimization dominates discourse, this focus on wisdom is both timely and essential.

A call to lead thoughtfully, not just quickly.

The rise of AI is relentless, but higher education can—and should—provide space for reflection. Assignments like “Segmenting the Wise Consumer” illustrate that how we teach AI is as important as what we teach. By grounding technical training in deep, human-centered questions, Luchs’ work shows that AI can be a tool for discovery, not just efficiency.

Students don’t just learn to use AI—they learn to question it, shape it, and understand its role in amplifying human insight. This is the future of business education: preparing students not only to solve problems, but to approach them with wisdom.

As AI becomes more prevalent, the focus must shift from simple adoption to thoughtful integration. Assignments like this provide a roadmap, showing how business schools can cultivate not just AI-enabled analysts, but wisdom-driven leaders.