Assistive communication technologies for individuals with multiple disabilities: an evidence mapping review informing future AI-enabled AAC.

OBJECTIVE: Assistive communication technologies are central to participation for individuals with multiple disabilities. Although artificial intelligence (AI) functionalities are increasingly proposed within augmentative and alternative communication (AAC) systems, empirical evidence for this population remains critically limited. This evidence mapping review synthesised research on aided AAC interventions involving individuals with multiple disabilities to identify technological trends, implementation patterns, and evidence gaps relevant to the future development of AI-enabled AAC systems. METHODS: Guided by PRISMA-ScR procedures, 36 peer-reviewed studies published between 1987 and 2025 involving individuals with co-occurring sensory, motor, and/or intellectual impairments were synthesised. Inter-coder reliability was strong (κ = 0.84). Structured coding and effect-direction mapping were used to identify technology modalities, implementation characteristics, and five recurring evidence patterns across the literature. Single-case experimental designs predominated (n = 14; 39%), and school-aged participants represented the largest group (44%). IMPACT: No studies directly evaluated AI-enabled AAC interventions, revealing a critical innovation-to-evidence gap. Communication outcomes were most strongly associated with modality-learner compatibility, multimodal access, and partner-mediated interaction rather than technological sophistication. Findings indicate that AI should be conceptualised as an adaptive support layer embedded within human-mediated communication systems rather than as an autonomous agent. These findings have direct implications for clinicians, assistive technology developers, and policymakers and provide a principled foundation for the responsible and equitable development of AI-enabled AAC systems.