GenAI in Indian higher education: faculty at the crossroads of adoption

Purpose The study examines the key factors influencing faculty members' intention to adopt Generative Artificial Intelligence (GenAI) in teaching within Indian higher education institutions. It focuses on faculty readiness, digital competence, and perceived usefulness in effective GenAI integration and development of future-ready classrooms. Design/methodology/approach Adopting a quantitative, cross-sectional design within a positivist paradigm, the study collected data from 455 faculty members using a structured and validated questionnaire. Data analysis employed IBM SPSS (Version 29.0) and IBM SPSS Amos (Version 26.0), with structural equation modeling applied to test the proposed theoretical framework. Findings Perceived usefulness, ease of use, and output quality primarily drive faculty members' adoption of GenAI, while social influence plays a minimal role. The study confirms the applicability of the Technology Acceptance Model (TAM) in this context and underscores the importance of experiential learning and institutional support in shaping adoption behavior. Practical implications The findings highlight the need for hands-on training, robust institutional frameworks, and inclusive policies that promote GenAI adoption in higher education. These efforts can improve instructional efficiency, reduce faculty workload, and encourage pedagogical innovation. Originality/value The study contributes a novel, faculty-focused perspective on GenAI adoption, shifting attention from student-centric research in developed countries to educators in India. Addressing geographic and thematic gaps offers context-sensitive insights essential for sustainable and inclusive GenAI integration in resource-constrained educational environments.