When AI Wears Many Hats: The Role of Generative Artificial Intelligence in Marketing Education
Unnati Narang et al.
Abstract
Generative artificial intelligence (GAI) is increasingly being integrated into marketing education and is reshaping the skill sets 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, the authors 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 model, they 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. The authors provide concrete examples for GAI's careful integration in marketing courses and discuss its implications for marketing educators, learners, and policy makers.
11 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.57 × 0.4 = 0.23 |
| M · momentum | 0.78 × 0.15 = 0.12 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.