  The field of Explainable Artificial Intelligence (XAI) often focuses on users
with a strong technical background, making it challenging for non-experts to
understand XAI methods. This paper presents "x-[plAIn]", a new approach to make
XAI more accessible to a wider audience through a custom Large Language Model
(LLM), developed using ChatGPT Builder. Our goal was to design a model that can
generate clear, concise summaries of various XAI methods, tailored for
different audiences, including business professionals and academics. The key
feature of our model is its ability to adapt explanations to match each
audience group's knowledge level and interests. Our approach still offers
timely insights, facilitating the decision-making process by the end users.
Results from our use-case studies show that our model is effective in providing
easy-to-understand, audience-specific explanations, regardless of the XAI
method used. This adaptability improves the accessibility of XAI, bridging the
gap between complex AI technologies and their practical applications. Our
findings indicate a promising direction for LLMs in making advanced AI concepts
more accessible to a diverse range of users.
