The Role of Artificial Intelligence in Modern Academic Research: A Systematic Review of Contemporary Literature (2015–2025) - Bayu Kurniawan; Fitri Wahyuni; Erin Putri Sosang; Nabilla Endmal Putri Iryas (Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya, 2026)
Background: The rapid advancement of artificial intelligence (AI) technologies, particularly large language models (LLMs) such as ChatGPT and other AIs, has fundamentally reshaped the landscape of modern academic research, raising both opportunities and critical challenges for higher education institutions worldwide. Aim: This study systematically maps the contexts in which AI has been applied in modern academic research during 2015–2025 and examines how AI has influenced the process and outputs of educational research over the past decade. Method: A Systematic Literature Review (SLR) design was employed, guided by the PRISMA protocol and PICOC framework. A total of 5,106 articles were identified during the initial ScienceDirect database search. Following a rigorous multi-stage screening process based on predefined inclusion and exclusion criteria, 19 articles were selected for final analysis. Results and Discussion: The findings reveal that AI has been applied across a broad and continuously expanding range of academic contexts, including automated writing assessment, citation prediction, AI-generated instructional content, academic integrity evaluation, and AI literacy development in academic libraries, with ChatGPT and similar LLMs serving as the primary catalysts of this expansion from 2022 onward. The influence of AI on educational research processes and outputs is simultaneously accelerative and disruptive: while AI demonstrably enhances efficiency, consistency, and productivity, it also poses serious threats to assessment integrity, authorship norms, and equity of access, particularly for international students and institutions from the Global South. Conclusion: AI is not merely a technical tool but a transformative force that demands systemic, ethical, and pedagogical responses across the entire academic ecosystem, including assessment redesign, integrated AI literacy curricula, and the development of coherent global ethical governance frameworks for AI use in academic research.