Explicating Generative Artificial Intelligence Literacy of Management Students in India

Purpose: It is apparent that Generative Artificial Intelligence (Gen-AI) is making its way into our daily lives. To navigate in an AI-influenced world and participate in future advances, students require a set of skills, known as AI Literacy, comprising using, applying, and communicating with AI. The current work discusses the future managers’ ability to understand and critically use Gen AI technologies with an emphasis on their technological, ethical, and socio-organizational dimensions. This literacy development is critical to students’ academic performance and their future success in the AI-enabled workplace. This paper’s objective is to assess the depth and quality of Gen-AI literacy among management students in India and find out whether demographic groups are comparable by level of GenAI literacy. Methodology: We used a quantitative cross-sectional design. Data were collected from management students from various Indian states through a questionnaire developed based on an established AI literacy scale. The scale successfully captured 6 dimensions of Gen-AI literacy: the social impact, execution, problem solving with Gen-AI, data literacy and AI ethics. Results: The findings reveal a moderate level of Gen-AI competency in management students. Respondents demonstrated greater awareness of social and ethical considerations, but less proficiency in problem-solving with Gen-AI software. No significant differences existed in Gen-AI proficiency by gender, family income, the background of parents or prior academic stream. Originality/Value: This study contributes to the growing domain of Gen-AI by evaluating the AI literacy of management students and supporting for improvement of students’ AI literacy levels. The present study achieved greater results by combining several methodological strengths, addressing persistent limitations in GenAI literacy research, and focusing on an underrepresented population. Keywords: AI Literacy, Generative AI, Literacy Assessment, Students’ Literacy, Management