Use of AI in teaching mathematics to persons living with disabilities: The Context of the United States

This narrative literature review investigates the integration of Artificial Intelligence (AI) in mathematics education for students with learning disabilities (SLDs) in the United States. Employing a narrative literature review methodology, the study synthesises peer-reviewed articles, policy documents, and grey literature published between 2020 and 2025, sourced from academic databases such as Google Scholar, Science Direct, Emerald, ERIC, and JSTOR. The review is grounded in Universal Design for Learning (UDL) and Constructivist Learning Theory, providing a theoretical framework for evaluating the role of AI in inclusive education. The selection criteria prioritised studies focusing on AI applications that enhance accessibility, personalisation, and early detection of learning difficulties, with special attention to tools like Photomath, Mathway, Socratic, Century, and the MACS Curriculum. The findings highlight AI’s capacity to support differentiated instruction, automate feedback, and facilitate early screening for conditions such as dyscalculia and dysgraphia. The review also identifies persistent challenges, including inconsistent classroom adoption, infrastructural and policy limitations, ethical concerns, and gaps in accessibility for some AI platforms. Comparative insights from international contexts, notably China, further underscore the importance of supportive policy frameworks and teacher training. The study concludes that while AI holds significant promise for transforming mathematics instruction for students with disabilities, realising its full potential requires sustained investment in accessible technologies, ongoing research, and collaborative policy development. The review advocates for responsible, equitable, and pedagogically sound AI integration to ensure all learners benefit from technological advancements in education.