When AI Wears Many Hats: The Role of Generative Artificial Intelligence in Marketing Education
2026-08-04 • Computers and Society
Computers and Society
AI summaryⓘ
The authors studied how Generative Artificial Intelligence (GAI) is being used in marketing education and suggested that it can play three main roles: as a tutor helping students understand concepts, as a teammate supporting group work, and as a tool for tasks. They found that each role affects how students learn and interact differently. The authors also highlight important ethical issues like data privacy and fairness that need attention. They provide examples and guidance for teachers, students, and policymakers to use GAI responsibly in marketing classes.
Generative Artificial Intelligencemarketing educationRole TheoryCommunity of Inquiry modeltutorteammateethical considerationsdata privacyplagiarismassessment fairness
Authors
Unnati Narang, Vishal Sachdev, Ruichun Liu
Abstract
Generative Artificial Intelligence (GAI) is increasingly being integrated into marketing education and is reshaping the skillsets required in marketing careers. While research has highlighted the promise and perils of incorporating GAI into education, there remains a need for a comprehensive framework to guide its effective use. In this research, we conduct a multipronged analysis, including a review of marketing course syllabi, a survey of marketing educators, and follow-up qualitative interviews. Building on Role Theory and the Community of Inquiry (CoI) model, we propose that GAI can assume three roles in marketing education: tutor, teammate, and tool. Each role influences teaching, social, and cognitive presence differently, shaping the learning experience and preparing workplace-ready marketing graduates. For instance, as a tutor, GAI can aid students in grasping theoretical concepts, while as a teammate, it can foster collaboration by supporting brainstorming and problem-solving activities. However, ethical considerations such as data privacy, plagiarism, dependency on AI, and fairness in assessment must be addressed to ensure its responsible adoption in marketing education. We provide concrete examples for GAI's careful integration in marketing courses, and its implications for marketing educators, learners, and policymakers.