<![CDATA[Generative artificial intelligence (GenAI) presents both opportunities and challenges for developing academic literacy in higher education. Unlike traditional academic literacy supports, which typically rely on human instruction, peer feedback, and independent writing processes, GenAI tools can generate, revise, and evaluate academic content in real time, fundamentally altering students’ engagement with writing and knowledge construction. However, the existing literature has not systematically examined how research on artificial intelligence (AI) and academic literacy has evolved over time or where key gaps remain. This scoping review investigates research continuity and gaps in studies of AI and academic literacy within undergraduate, humanities-related higher education contexts, comparing publications from 2022–2024 with those published in 2025. Guided by the PRISMA extension for scoping reviews, a total of 2,026 records were retrieved, of which 56 empirical studies published between Jan 1st 2022 and Oct 31st 2025 were included for analysis. The studies were examined across two time periods (2022–2024 and 2025) to analyze publication trends, geographical distribution, methodological approaches, and pedagogical themes. The findings indicate a rapid expansion of research following the emergence of large language model–based tools, such as ChatGPT. Early studies primarily focused on AI-supported writing processes, user adoption, and efficiency, whereas more recent research increasingly emphasizes critical AI literacy, responsible AI use, and human–AI collaboration in learning contexts. The review also revealed significant geographical and methodological imbalances in the literature. These findings suggest that future research should prioritize methodological diversity, stronger theoretical grounding and broader sociocultural representation. Higher education institutions are encouraged to integrate AI literacy into academic literacy instruction and develop clear policies that support the responsible and pedagogically effective use of AI technologies.]]>
