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September 19, 20250 citationsOpen Access

Artificial Intelligence for Accessibility: A Comprehensive Systematic Review and Impact Framework for Assistive Technologies

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BBBandaru BhavanaKAKeerti AnkolekarBUBiradar Usha

Key Points

  • AI-powered assistive technologies significantly enhance usability and effectiveness in various accessibility domains.
  • The new Accessibility Impact Score indicates that visual and motor applications had the highest effectiveness scores.
  • This review followed PRISMA guidelines to analyze 40 peer-reviewed studies for comprehensive insights.
  • Findings highlight the need for ethical and inclusive AI development to ensure broad accessibility benefits.

Abstract

Artificial Intelligence (AI) is transforming assistive technologies into intelligent systems that enhance accessibility across visual, auditory, motor, and cognitive domains. This review examined 52 works published between 2023 and 2025, with 40 peer-reviewed studies systematically analyzed using PRISMA guidelines. The Accessibility Impact Score (AIS) was introduced as a novel framework to evaluate usability and effectiveness. Findings show that AI-powered tools such as smart glasses, adaptive exoskeletons, and multimodal learning platforms outperform traditional assistive devices. Visual and motor applications achieved the highest AIS values, while auditory and cognitive tools demonstrated strong emerging potential. The integration of multimodal AI, including voice, vision, haptics, and brain–computer interfaces, enables proactive and context-aware support. These results highlight AI’s role in enhancing independence, social participation, and quality of life. The review also emphasizes the importance of open datasets for reproducibility and the need for ethical, inclusive, and scalable adoption of AI in accessibility. Overall, AI offers a paradigm shift toward inclusive, human-centered assistive systems with potential applications in healthcare, education, and daily living.

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Cite This Study

Bhavana et al. (2025) studied this question.

synapsesocial.com/papers/68d466a831b076d99fa64f5bhttps://doi.org/10.33971/ijmrai.1.2.16
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