Quantitative analysis investigates drivers of generative AI adoption in Indian higher education, suggesting implications for marketing and policy.
Adoption of artificial intelligence (AI) is transforming the ways of learning, teaching and academic support delivery in higher education institutions (HEIs). Platforms like IBM Watson, Google Bard, Microsoft Azure AI and Amazon Lex have significantly enhanced customised learning, automated administration and student engagement. Following these advancements, Generative AI (GenAI) and Responsible AI now evoke excitement and apprehension, most notably regarding ethical standards, explainability and user trust. The primary objective of this research is to investigate the key drivers of GenAI adoption in Indian HEIs. A quantitative method was applied using an anonymous self-completion online survey to collect primary data from 401 lecturers and 332 students. Structural Equation Modelling (SEM) was used to analyse the data. The hypotheses supporting H[Formula: see text], H[Formula: see text], H[Formula: see text], H[Formula: see text] and H[Formula: see text] were confirmed through analysis. Transparency marketing also acted as a mediator between the intention to use GenAI and trustworthy AI. The implications are important for marketing strategists, policy-makers and higher education academic managers. Managerially, GenAI adoption improves learning performance and promotes institutional branding, student satisfaction, enrolment expansion and competitive advantage in the education market. The research suggests policies to increase the gains of GenAI and reduce its harms to promote sustainable innovation in higher learning.
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Dwivedi et al. (2026) studied this question.
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