Transforming Research Management and Knowledge Creation With Large Language Models
Tayeb Brahimi, Akila Sarirete, Naila Marir
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Source: Crossref
Published: Oct 20, 2026
DOI: 10.1108/978-1-83662-878-120261008
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Abstract The rapid advancement of Large Language Models (LLMs) has fundamentally transformed academic research and institutional operations. Major LLMs, such as OpenAI’s ChatGPT, Anthropic’s Claude, Google’s Gemini, and Microsoft Copilot, are now integrated into educational institutions at research and administrative levels. These LLMs go beyond summarizing text or polishing emails to include personalized learning, automated content creation, decision-making, and pedagogical integration. This chapter investigates the evolving role of LLMs in transforming the research landscape, particularly in academic writing, research management, pedagogy, evaluation, and ethical consideration. The research method is based on a systematic literature review (SLR) following PRISMA protocols, supported by bibliometric analysis and keyword-based thematic analysis of peer-reviewed articles from Web of Science and Scopus databases (2020–2025). Results revealed the existence of five major themes, namely academic writing and content generation, research evaluation, pedagogical integration, model comparison, and ethical considerations. The study highlights a sharp increase in publications since ChatGPT’s emergence, with thematic shifts toward education-related applications. Heatmaps across Scopus and WoS demonstrated significant trends toward real-world educational applications. However, ethical concerns showed strong growth, reflecting academic integrity issues. The keyword co-occurrence analysis also showed a dynamic research landscape with strong thematic ties to ethics, academic writing, teaching, and educational innovation. The overlay visualizations further illustrated the temporal evolution of topics from foundational concepts toward technology adoption, user experience, and collaborative learning. This chapter concludes by suggesting some recommendations to guide institutional policy and future research, ensuring an effective integration of LLMs in academic settings.
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