The 4Ps in Teaching Business: Building Effective Pedagogical Relationships with AI We introduce the 4Ps Framework—Planner, Prospector, Processor, and Portal—as a pedagogical tool for developing AI partnership literacy across business and management education. The framework derives from two theoretical pillars: March's (1991) exploration-exploitation distinction and human-AI collaboration research (Wilson & Daugherty, 2018), which identifies locus of generativity—whether humans or AI originate the initial conceptual structure—as the key partnership decision. Crossing these dimensions yields four distinct modes:
- Planner – Human-led, efficiency: students direct analysis; AI executes.
- Prospector – Human-led, exploratory: students frame inquiry; AI expands possibilities.
- Processor – AI-led, efficiency: AI handles routine tasks, freeing students for higher-order thinking.
- Portal – AI-led, exploratory: AI generates unexpected frameworks for students to critically evaluate.
The framework emerged from iterative observation across multiple semesters, two institutions, three instructors, and courses in strategic management, international business, and international marketing. Qualitative reflections show that deliberate exposure to all four modes produces synergistic gains in domain knowledge and AI collaboration competencies—without requiring technical expertise.
Dr. Jack Marr is a Clinical Associate Professor of International Business and Global Programs Director at the College of Business and Economics, Boise State University. His current research focuses on AI integration in management education, the geopolitics of emerging technologies—including quantum computing and semiconductors—and U.S.-China economic relations. He is an active researcher, teacher, and practitioner on how generative AI is reshaping both business education pedagogy and the competitive dynamics of global technology industries. Jack is a frequent public speaker and advisor on international business and technology policy.
Steven Hyde, Ph.D. is an associate professor in the College of Business and Economics at Boise State University. His research develops new approaches for studying executive behavior and decision-making using artificial intelligence. This work spans three areas:
- Creating theory-driven machine learning measures of executive characteristics and behaviors,
- Examining how AI is transforming business practice and education, and
- Investigating how executive and board characteristics influence firm outcomes.
His work appears in Strategic Management Journal and Journal of Applied Psychology, and has been covered by Fast Company, The Atlantic, and The Boston Globe.
Target Group: Lecturers
