Writing, as a form of human communication, has long served as a vessel to preserve human thoughts, cultures and societal structures. It encompasses fictional and non-fictional expressions of reality and imagination. These expressions can be realized through a deliberate process of arranging words into meaningful structures. Traditional writing, using paper and pencil, involves complex cognitive skills and prescriptive norms to curate a draft coherently at a certain point in time. This process of writing can be challenging, particularly for non-native English writers who mostly, if not always, struggle with structuring an argument with suitable words and grammar (Tso et al., 2016; Rafi and Moghees, 2022).Although traditional writing can often be time-consuming, especially in formal contexts, such as academic and professional domains, it has undeniably played a vital role in the advancement of human intellectual development and literacy since its inception. Closely intertwined with writing is the process of translation, which in many ways bridges linguistic and cultural divides. It makes knowledge accessible to linguistically diverse audiences. Certainly, translation is not only a linguistic substitution but also a form of writing that requires deeper understanding, interpretation and reconstruction of meanings in the target language. Both writing and translation are integral to formal communication, literacy and transmission of ideas in multilingual societies (Chen and Yan, 2024).With the advent of technology, writing and translation evolved through mediated tools, such as typewriters and keyboards. These tools streamlined the presentation and preservation of ideas. Even then, these tools required the writers' active role in organizing and structuring thoughts. The most transformative phase to date is AI-assisted writing and translation. Powered by large language models (LLMs), AI tools, such as ChatGPT, Grammarly and DeepSeek, among others, generate human-like writing and translation. Based on biomatrix analysis of research trends from 2015 to 2024, Mittal et al. (2026) have found that highly cited studies are concentrating on GenAI while indicating a thematic shift towards its literacy, academic integrity and ethics in academic research. These findings align with earlier studies (Ng et al., 2021, 2022 and those cited therein) that emphasize the importance of GenAI literacy in writing to enable responsible and effective adoption of GenAI.GenAI serves as a co-creation avatar in writing literary pieces, self-publishing and marketing (Grundy, 2026). This showcases its transformative potential in the creative writing industry. Furthermore, Grundy (2026) has emphasized that authors no longer need a completed manuscript to pitch to agents or publishers. With the assistance of AI tools, they can independently handle editing, marketing and distribution. Beyond transforming publishing and marketing processes, the adoption of AI in education has also shifted the teaching of writing. Nyaaba et al. (2026) propose an innovative text-to-video GenAI framework designed to support culturally and linguistically responsive pedagogy for the growing population of English language learners in the United States of America. This transformation has also influenced educators to upgrade their teaching and assessment methods (Deepshikha, 2026). Now employers, more than ever before, want graduating students to be proficient in the use of AI tools to improve their productivity and performance. It is, therefore, important for educators to clearly delineate for students what levels of GenAI use are acceptable or unacceptable (Rafi and Amjad, 2025; Rafi and Khalil, 2026; Roe et al., 2026).Pedagogical approaches must move beyond purely technical instruction towards the systematic cultivation of creative and critical thinking. Yang et al. (2026) have argued that learners should be guided in the effective use of GenAI for critically interrogating its outputs, questioning its assumptions, and reflecting on its influence on cognition and language practices. This shift calls for scaffolded, reflective, and responsive pedagogical approaches that integrate existing teaching methods and approaches with the affordances of emerging technologies. Yamson et al. (2026) emphasize striking a balance between academic integrity and GenAI integration as well as explicit ethical rules and creative assessment techniques.There is considerable knowledge within GenAI, and it can be drawn out through effective prompts. This necessitates that educators must develop students' competencies in various methods of prompt formulation as advocated by Mabrito (2024) and Walter (2024). Such instruction not only enhances the confidence of students in integrating GenAI into their writing process but also promotes a more effective application of AI tools in their scholarly pursuits, inter alia, papers, theses and creative writing. Federiakin et al. (2024) emphasize that prompt engineering is an emerging skill essential for personal and professional learning development of students in the 21st century, as also supported by Knoth et al. (2024). This skill will empower them to produce precise and contextually relevant outputs for minimizing the potential for AI hallucinations when extracting content from a variety of knowledge bases (Lee and Palmer, 2025).To integrate GenAI meaningfully into research writing and translation in higher education, users must move beyond ad hoc prompting toward more structured forms of dialogic engagement with LLMs. Prompting is a form of cognitive scaffolding, like a primary school teacher who guides their learners through carefully sequenced questions. A well-designed question ignites a well-thought-out answer, albeit structured reasoning and a personalized learning path. Educators must act as epistemic mediators. They must train learners to understand the applications and limitations of GenAI while valuing the strength of human agency and epistemic independence (Rafi and Khalil, 2026).Scerri et al. (2026) recommend that a specialized pedagogy-aware AI system can outperform generic chatbots in educational settings. The traditional prompt formulation paradigms such as retrieval augmented generation, including chain of thought, reasoning and action and directional stimulus prompting, can be understood as complementary modes of epistemic scaffolding. However, GenAI must support rather than replacing core intellectual skills while offering mentorship provision beyond classroom hours (Scerri et al., 2026).It is important to highlight that there are several forums such as Alison, Coursera, edX, FutureLearn, Google, Harvard, etc., which offer online courses regarding how to critically engage with GenAI and master the art of prompt engineering. While mastering prompt formulation methods, users must be aware of the limitations of GenAI, including data privacy, unethical practices and institutional regulations for utilizing AI-powered tools. There is a pressing need to address equity and access, particularly in underresourced regions (Tabiri et al., 2026; Yamson et al., 2026), to ensure GenAI is not limited to technologically advanced institutions.The papers published in this special issue (also cited in this editorial) offer rich insights across diverse disciplinary contexts and highlight a range of methodological perspectives that showcase the transformative role of GenAI in academic writing, translation, and literacy in higher education. These studies recommend universities establishing clear GenAI-assisted writing and translation policies while integrating AI literacy into curricula, promoting human-AI collaboration in research, training educators to assess AI-assisted work and adopting alternative assessments like oral defence and portfolios to ensure originality, critical thinking and scholarly integrity. These initiatives will safeguard intellectual property rights for future writers by preserving their authorship, research originality and data ownership.Furthermore, universities need to develop guidelines and allocate budgets for acquiring AI licences that support the establishment of human and GenAI dialogical spaces, ideally, within their libraries (O'Dea et al., 2025). This initiative will help promote deeper engagement and reflection throughout students' learning journey while simulating AI tools to them as supported by El Idrissi and Alami (2026) in the context of management students' academic productivity. Universities should also train them through writing courses, workshops and seminars regarding how to open up a dialogue for academic writing and translation, widen it while engaging with their educators and GenAI and deepen it for reflecting on their feedback (Vu and Vu, 2026). These strategies will help scaffold GenAI literacy practice, pedagogical insights and a culture of robust scholarship for writing and translation in higher education institutions (Ng et al., 2024a, b).
Rafi et al. (Mon,) studied this question.