Use of AI in improving website accessibility : a systematic literature review and conceptual framework for digital inclusion
Ali, Muhammad (2025)
Diplomityö
2025
School of Engineering Science, Tietotekniikka
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe20251112107465
https://urn.fi/URN:NBN:fi-fe20251112107465
Tiivistelmä
The thesis examines how artificial intelligence (AI) can help in enhancing website accessibility and also bridge the gap between different established standards like Web Content Accessibility Guidelines (WCAG 2.2), and its practical implementation. Despite the legal frameworks E.g European Accessibility Act (2025), there are many websites which still fail to meet the basic accessibility requirements. The study explains how AI can help in personalizing user experiences and simplifying content for people with different disabilities.
A Systematic Literature Review (SLR) using PRISMA 2020 protocol was conducted in which 43 studies were analysed which were published between 2018 - 2025. Findings group AI applications into 5 categories: computer vision, speech technologies, natural language processing (NLP), AI-based accessibility testing and, adaptive and personalized interfaces. These techniques help improve accessibility in different ways explained in this thesis.
Results indicate that AI adds personalization, scalability, and innovation to accessible web design. This thesis produces a taxonomy of artificial intelligence (AI) techniques and also shows a direction for policymakers, researchers and developers. It concludes that AI should accompany but not replace human centered evaluation and design to make sure technology improves digital inclusion instead of superficial compliance.
A Systematic Literature Review (SLR) using PRISMA 2020 protocol was conducted in which 43 studies were analysed which were published between 2018 - 2025. Findings group AI applications into 5 categories: computer vision, speech technologies, natural language processing (NLP), AI-based accessibility testing and, adaptive and personalized interfaces. These techniques help improve accessibility in different ways explained in this thesis.
Results indicate that AI adds personalization, scalability, and innovation to accessible web design. This thesis produces a taxonomy of artificial intelligence (AI) techniques and also shows a direction for policymakers, researchers and developers. It concludes that AI should accompany but not replace human centered evaluation and design to make sure technology improves digital inclusion instead of superficial compliance.