Aug 2026· Applied Informatics· 0 citations· 47 references
TL;DR
The paper presents the AI Literacy Leadership Framework (AILLF), which conceptualises AI literacy as a multidimensional leadership capability comprising technical, strategic, ethical, and applied dimensions that support four interconnected leadership domains: innovation, decision-making, ethical governance, and policy development.
Abstract
The integration of Artificial Intelligence (AI) in higher education is reshaping institutional decision-making, governance, policy development, and educational innovation. Effective leadership in AI-enabled environments requires more than technical competence, extending to strategic awareness, ethical judgement, and the ability to critically evaluate the broader implications of AI technologies. Drawing on survey and interview data from 52 academic leaders across UK higher education institutions, this study examines current levels of AI literacy and explores how AI capability relates to institutional readiness and leadership practice. The findings reveal variation in participants’ self-reported AI literacy and engagement, identify technical, strategic, ethical, and organisational capability gaps, and highlight structural barriers including limited time, fragmented professional development, and insufficient institutional support for institution-wide AI adoption. In response, the paper presents the AI Literacy Leadership Framework (AILLF), which conceptualises AI literacy as a multidimensional leadership capability comprising technical, strategic, ethical, and applied dimensions that support four interconnected leadership domains: innovation, decision-making, ethical governance, and policy development. Informed by leadership theory, international AI governance frameworks, and the study’s exploratory empirical findings, the AILLF is accompanied by a proposed capability progression model and role-differentiated leadership competency guide to provide implementation guidance for higher education institutions. The study contributes an empirically informed conceptual framework that integrates AI literacy, leadership theory, and AI governance, providing a foundation for future research and institutional approaches to AI leadership within higher education.
The framework 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.
Kuldeep Kaur, P. Pundir· International Journal For Mu...· 1 citation
The framework demonstrates that the sustainable value derived from AI in higher education depends less on the level of the technology adopted than on the ethical bases and consistency of the leadership responsibility for its integration, offering higher education leaders and policymakers a structured path toward respon...
Asem S. Obied, Ahmed Raja Haj Ali· Frontiers in Education· 0 citations
It is argued that AI strengthens leadership through evidence-based decision-making, forecasting, fraud detection, educational innovation, healthcare support, and improved governance, but cannot replace human qualities such as ethical judgment, empathy, accountability, cultural understanding, integrity, integrity, and w...
H. Idris· IC-BESTS: International Conf...· 0 citations
The ability of institutions to leverage opportunities to transform governance in higher education depends on adopting anticipatory governance models that emphasize foresight and stakeholder engagement, as well as adopting changes to the traditional role of both leaders and educators to become data literate, inclusive,...
S. Baroudi· International Journal of Edu...· 2 citations
The article proposes the concept of the "augmented leader" and develops a four‐competency framework for AI‐integrated leadership: algorithmic literacy, strategic use of AI, ethical leadership and governance, and culture and adoption.
David López-López, P. Garcia, Miguel Saiz Garcia et al.· New Directions for Student L...· 0 citations
Purpose: This paper develops a theory-informed conceptual framework for responsible AI entrepreneurship ecosystems in higher education. It addresses the limited integration of AI capabilities, entrepreneurship, institutional readiness, and governance in existing scholarship, particularly amid increasing AI adoption by...
Oluwatosin Omosolape Omodewu, M. Shokunbi· Elicit Journal of Economics...· 0 citations
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