Responsible AI Readiness in Higher Education: A Multilevel Framework Integrating Faculty Capability, Professional Judgement and Institutional Conditions

Abstract

The increasing use of artificial intelligence (AI) and generative artificial intelligence (GenAI) is reshaping teaching, assessment, curriculum development, research, academic administration and professional learning within higher education. Yet existing approaches to AI literacy, competence, self-efficacy, adoption and ethics remain conceptually dispersed, limiting a coherent understanding of faculty preparedness for responsible AI-mediated professional practice. This paper addresses this gap by conceptualising Responsible AI Readiness (RAIR) as a higher-order professional capability that integrates AI knowledge and competence, self-efficacy, ethical judgement, pedagogical preparedness, human agency, privacy and fairness within enabling institutional conditions. Drawing on a critical integrative review of conceptual, empirical, measurement, policy and competency-framework literature, the paper develops a multilevel architecture comprising seven faculty-level dimensions: AI Knowledge and Literacy, AI Self-Efficacy, Responsible and Ethical AI Awareness, Human Agency and Professional Autonomy, AI Pedagogical Readiness, Data Privacy and Security Awareness and Bias and Fairness Awareness. These capabilities are situated within two contextual conditions- Institutional AI Support and Institutional AI Governance Readiness, thereby connecting individual capability with the organisational environments within which AI-mediated professional decisions occur. The framework advances a measurement-oriented conceptualisation of RAIR as a potentially testable higher-order construct and proposes a pathway towards scale development, psychometric validation, multimethod assessment, measurement invariance and subsequent multilevel modelling. Its principal contribution is to move the discourse beyond AI literacy and technology adoption towards integrated competence, responsible professional judgement and institutionally enabled readiness. The framework further provides an India-contextualised perspective connecting faculty AI capability with responsible innovation, human-capital development and the Viksit Bharat@2047 vision while offering a transferable conceptual basis for research on human-centred and sustainable AI transformation in higher education.