AI-Enabled Inclusive Library Services (AILS) Framework: Enhancing Accessibility and Inclusivity in Teacher Education

The integration of artificial intelligence (AI) in higher education offers new opportunities to enhance accessibility and inclusivity, particularly in teacher education programmes that prepare future educators to serve diverse learners. Although prior research has examined AI in libraries, Universal Design for Learning (UDL), and inclusive teacher education, limited studies explore their intersection within academic library contexts. This paper introduces the AI-Enabled Inclusive Library Services (AILS) Framework, a conceptual model designed to support accessibility and inclusivity in teacher education libraries. Grounded in UDL principles, international disability rights frameworks such as the UN Convention on the Rights of Persons with Disabilities, and global inclusive education policies, the framework positions libraries as both service providers and experiential learning environments for pre-service teachers. The AILS framework comprises seven interconnected components: foundational principles, contextual stakeholders, AI capabilities, library services and touchpoints, institutional capacity and governance, outcomes and evaluation, and feedback and adaptation. By incorporating AI technologies such as natural language processing, text-to-speech systems, recommender algorithms, and multilingual tools, the framework addresses barriers faced by students with disabilities and diverse learning backgrounds. Beyond improving resource accessibility, AILS models inclusive pedagogical practices for future educators and aligns with Sustainable Development Goals 4 and 10. The framework offers a globally adaptable approach for developing inclusive, AI-enabled library services in higher education.