Utilization of Artificial Intelligence and Assistive Technology in Autism: Diagnosis, Treatment, and Education Applications—A Systematic Literature Review

Utilization of Artificial Intelligence and Assistive Technology in Autism: Diagnosis, Treatment, and Education Applications—A Systematic Literature Review

Article Number: e2025350 | Available Online: July 2025 | DOI: 10.22521/edupij.2025.17.350

Mohammad A. Beirat , Ahmad Algolaylat , Hussein Al Njadat , Bassam AlAbdallat , Alaa K. Al-Makhzoomy

Full text PDF | 7697 | 1149

Abstract

Background/purpose. This paper systematically reviews current advancements in AI-based diagnostic tools and assistive technologies, analyzing their influence on the early detection, treatment, and educational support of autism spectrum disorders (ASDs). The review aims to identify both the benefits and challenges of incorporating these technologies into autism care and to highlight future opportunities, especially in enhancing learning and communication outcomes for individuals with autism.

Materials/methods. A systematic literature review was conducted based on 27 peer-reviewed articles published between 2010 and 2023. The search strategy involved major databases, including Scopus, ScienceDirect, PubMed, JSTOR, and Google Scholar. The analysis follows the PRISMA approach, with specific inclusion criteria and quality assessment procedures in place. The study focuses on four key subthemes: AI-driven diagnostic systems, therapeutic and assistive robotics, educational and communication applications, including augmented reality applications, and ethical and implementation challenges associated with autism-related technologies.

Results. The reviewed studies demonstrate that AI tools offer significant potential for early and precise autism diagnosis, particularly through the application of machine learning algorithms to behavioral and physiological data. Assistive technologies, particularly social robots and AR platforms, show positive outcomes in therapeutic engagement. Supporting educational development and skill acquisition. However, issues such as limited accessibility, ethical concerns regarding data privacy, and integration barriers persist.

Conclusion. AI and assistive technologies are transformative in autism care, offering innovative solutions for diagnosis and treatment. However, their successful implementation requires addressing ethical, infrastructural, and cultural challenges. This study provides evidence-based insights and practical recommendations for researchers, clinicians, educators, and policymakers to enhance the equity and impact of these emerging technologies in autism intervention and inclusive learning environments.

Keywords: Artificial intelligence, assistive technologies, autism diagnosis, therapeutic interventions, ethical frameworks, special education

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