The growing use of Artificial Intelligence (AI) in EFL academic writing, particularly ChatGPT, has changed how students generate and organize written texts. However, it remains unclear how academic writing components organization, logical development of ideas/content, grammar, punctuation, spelling, and mechanics, and style and quality of expressions are manifested in ChatGPT-assisted essays and which components are most and least evident, especially in cause-and-effect essays that require clear logical relationships. This study aims to examine how academic writing components are manifested in ChatGPT-assisted cause-and-effect essays and to identify which components are most and least evident. This study employed a descriptive qualitative approach using Qualitative Content Analysis (QCA) with a deductive orientation. The participants were 21 third-semester students of the English Education Study Program at Universitas Muhammadiyah Kotabumi who used ChatGPT in writing their cause-and-effect essays. The researcher used an analytical writing rubric adapted from Brown (2004) as the research instrument. The data were analyzed through data condensation, data display, and conclusion drawing. The findings show that all components are present but appear at different levels of consistency. Organization and logical development of ideas/content emerge as the most evident components, style and quality of expression appear at a moderate level, while grammar and punctuation, spelling, and mechanics remain the least evident. These findings indicate that ChatGPT supports idea organization and development more effectively than grammatical and mechanical accuracy. The results demonstrate that ChatGPT facilitates students in organizing and developing ideas. However, it does not fully ensure grammatical accuracy or effective revision. Therefore, students should position ChatGPT as a supporting tool while continuously improving their language accuracy and revising their writing.