What is it about?
Since the release of tools like ChatGPT in late 2022, academic writing has changed, but it has been unclear exactly who is adopting these technologies and why. In this study, we surveyed 823 social scientists to understand their real-world usage of AI for writing. We discovered a significant "generational divide." The data reveals that researchers in their 20s are more than twice as likely to use AI tools compared to their colleagues in their 60s. The study suggests that this isn't just about tech-savviness; it is about survival. Younger researchers face immense pressure to "publish or perish" to secure their careers, making AI an attractive tool for efficiency. Conversely, senior researchers, who are already established, tend to stick to traditional writing methods. This creates a disconnect in higher education: if senior professors do not use or understand the tools their students rely on, it becomes difficult to mentor them effectively or evaluate their work fairly. This research highlights the need for universities to adapt their policies and mentorship models to bridge this growing gap.
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Why is it important?
This study provides the first systematic, population-level quantification of age-related differences in AI adoption for academic writing. While existing literature often focuses on theoretical ethics or student plagiarism, our work offers empirical evidence on how faculty and researchers are actually using these tools. Uniquely, our analysis demonstrates that age (rather than gender or academic rank) is the primary predictor of AI adoption. This distinction is timely and critical for university leadership and policymakers. It suggests that blanket policies banning or mandating AI may fail because they ignore the asymmetric pressures facing different generations. Junior researchers view AI as a necessity for meeting productivity metrics, while senior faculty may view it as a threat to scholarly integrity. By identifying this structural friction, our work alerts the academic community to a looming crisis in peer review consistency and the "apprenticeship" model of PhD supervision. If left unaddressed, this divide could lead to a fragmentation of scholarly standards where different generations no longer share a common definition of academic writing.
Perspectives
Working at the intersection of social science and technology, I have witnessed firsthand the silent tension in department hallways: junior colleagues quietly using AI to meet impossible deadlines while senior mentors express skepticism about AI writing. We wrote this paper to move beyond anecdotes and put hard numbers to this phenomenon. What I find most compelling, and concerning about our findings is the potential loss of "tacit knowledge." If the next generation of scholars outsources the cognitive struggle of writing to AI, and the current generation of mentors refuses to engage with those tools, we risk breaking the chain of knowledge transfer that defines academia. I hope this article encourages senior scholars not just to critique AI, but to learn it, if only to better guide the students who have no choice but to use it.
Dr. Marko Galjak
Read the Original
This page is a summary of: Generational Divide in AI Adoption for Academic Writing: Evidence From Serbian Social Scientists, Social Science Computer Review, December 2025, SAGE Publications,
DOI: 10.1177/08944393251413796.
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