<p>The integration of generative artificial intelligence (GenAI) for dissertation writing has sparked debates regarding where it can augment the writing process, which must exclusively have human intelligence at its core, and how to write GenAI prompts that produce effective output. The present study’s exploration of this topic is based on qualitative data gathered from a survey of 86 doctoral students and 7 thesis supervisors in the social sciences and humanities disciplines. We applied the AI Assessment Scale developed by Perkins et al. (2024) to evaluate GenAI’s role across various stages of doctoral dissertation writing and to explore pedagogical adaptations of GenAI to support dissertation writing in the contexts of the social sciences and humanities. Our findings indicate that GenAI can be fully utilized to improve writing mechanics, including grammar, structure, and coherence, by enhancing clarity and efficiency. GenAI also proves beneficial in analyzing larger datasets by defining a coding frame, identifying trends, and conducting sentiment analyses. GenAI can be utilized in argument structuring by organizing literature, suggesting logical ways to arrange sentences, and generating counterarguments. The participants agreed that exploring these applications saved their time and allowed them to focus on a deeper intellectual engagement. However, they recommended limiting or prohibiting GenAI use in areas that require critical reasoning, originality, and cultural context. Moreover, they underscored that AI-generated content may lack accuracy and contextual depth, thus requiring careful human validation against vague expressions. This study focuses on prompt literacy and provides a scale to utilize GenAI for doctoral dissertation writing.</p>