Investigating LLM-based tools to support Usability, Accessibility, User Experience in HCI activities: A Systematic Literature Mapping

Abstract

This study presents a Systematic Literature Mapping (SLM) of recent research on the application of Large Language Models (LLMs) within Human–Computer Interaction (HCI). Drawing from 104 peer-reviewed articles published between 2021 and 2025 in the ACM Digital Library and IEEE Xplore, the mapping investigates the role of LLMs in supporting usability, accessibility, and user experience (UX) activities. LLMs, rooted in Natural Language Processing (NLP), have demonstrated widespread utility across various domains, including healthcare, education, and software engineering. Within HCI, their applications include conversational agents, accessibility enhancements, user journey modeling, prototyping tools, and adaptive user interfaces. The findings highlight how UX professionals have integrated LLM-based solutions into design workflows, leveraging these technologies for improved engagement, personalization, and collaboration. This research addresses 4 guiding questions concerning the domains of application, methodologies, and practitioner adoption of LLMs. The study contributes by (i) offering a comprehensive mapping of HCI-related LLM literature, (ii) identifying areas of active research, and (iii) uncovering emerging trends and open challenges that may inform future investigations.

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