<p>The study aims to develop Epistemic Trust in Generative AI for Higher Education Scale (ETGAI-HE Scale) in the context of Indian higher education. The study utilizes a multistep strategy to develop the scale, applying EFA and CFA. The Maximum Likelihood method with ProMax rotation was applied in EFA. CFA was performed and fit indices were calculated. The study established an integrative theoretical framework for measuring epistemic trust in AI in higher education by reviewing the literature of epistemic trust and its historical evolution and validating it with EFA and CFA. Six factors emerged as dimensions of epistemic trust in AI. Cognitive Evaluation of Trustworthiness (ETAI), Interpersonal and Contextual Influences (ICI), Dependability and Safety (DS), System Predictability &amp; Transparency (SPT), Performance Expectation (PE) and User Control and Autonomy (UCA). Overall Cronbach’s Alpha (α) was 0.823 which supports the reliability of the instrument. The scale’s convergent validity was established by calculating the average variance extracted (AVE) and discriminant validity was established using heterotrait–monotrait (HTMT) ratio. The validated six-factor model explained 70.8% of the total variance. The study proposes an integrative framework to measure epistemic trust in AI and provides a tool to assess the level of trust of students, researchers and teachers although implementing AI enhanced curriculum and research policies. This tool is first to propose an integrative framework to measure epistemic trust in generative AI in higher education context.</p>