The Impact of Artificial Intelligence on Neuroinclusion in the Cybersecurity Industry

Abstract

As artificial intelligence became increasingly integrated into cybersecurity operations, this study examined its impact on workplace inclusion for neurodiverse professionals. The research addressed the problem that AI systems, often developed with neurotypical assumptions, could unintentionally exclude or disadvantage employees with diverse cognitive profiles. The purpose of this qualitative case study was to explore how AI design influenced neuroinclusion in cybersecurity workplaces. Grounded in Cognitive Load Theory, Socio-Technical Systems Theory, and the Theory of Technology Inclusion, the study investigated three research questions focused on standardizing AI design, identifying challenges in AI use, and examining AI’s impact on workplace inclusion. Data were collected through document analysis and interviews with a purposive sample of cybersecurity professionals recruited through The Cyber Guild. Thematic analysis, guided by Braun and Clarke’s six-phase framework, was used to identify key themes and patterns across the data. Results indicated that inclusive AI design required adaptability, transparency, and alignment with supportive organizational policies. Findings revealed that neuroinclusive systems reduced cognitive strain and improved workplace participation, while rigid or opaque systems reinforced exclusion and mistrust. The study concluded that intentional design and governance of AI could enhance both inclusion and performance in cybersecurity. Recommendations included establishing ethical boundaries for AI decision-making, embedding neuroinclusion in policy and training, and leveraging inclusive design to address the cybersecurity talent shortage. These findings contributed practical and theoretical insights for advancing ethical and neuroinclusive AI development