AI-Driven solutions for transition and employment support in students with autism: Global case studies from Auticon and Mathisis

Abstract

Students with Autism Spectrum Disorder (ASD) often face substantial barriers in transitioning from secondary education to employment, including challenges in communication, adaptability, and access to individualized support. As artificial intelligence (AI) technologies gain momentum in education and workforce development, they present new opportunities to address these challenges through personalized, scalable interventions. This paper examines two global case studies Auticon, a neurodiverse IT consultancy employing AI-based job-matching systems, and Mathisis, a European Union-funded adaptive learning platform for students with special needs. Through a comparative case study methodology, the paper explores how AI tools can support vocational preparation and individualized learning by aligning content and opportunities with learners’ strengths and emotional needs. Findings highlight the importance of personalization, integration of human support, and ethical implementation practices. The paper concludes with recommendations for educators, policymakers, and developers seeking to implement AI-driven solutions that enhance transition services and employment outcomes for autistic students. While previous studies have discussed AI applications in education or autism support separately, this paper contributes a novel perspective by synthesizing real-world case studies that apply AI specifically in vocational transition contexts for autistic individuals. The comparative analysis of Auticon and Mathisis provides practical insights into scalable, culturally relevant, and ethically grounded practices, offering a preliminary framework for designing inclusive AI-supported transition models.