Benefits and challenges of using generative artificial intelligence tools in scientific research: A systematic review

Document Type : Original Article

Author

Department of Theory-Oriented STI Studies, National Research Institute for Science Policy, Tehran, Iran

10.22091/stim.2025.12295.2213

Abstract

Objective: This study aimed to examine the opportunities and challenges associated with the use of generative artificial intelligence (GenAI) tools in scientific research and scholarly outputs.
Method: A systematic review was conducted by searching international scientific databases, including Google Scholar, ScienceDirect, Web of Science, and Scopus. Following the retrieval of relevant articles and screening based on the predefined inclusion and exclusion criteria, 41 articles were selected for qualitative meta-synthesis. The selected articles were carefully reviewed, and open and axial codes were extracted. During open coding, all relevant categories were identified, while axial coding was used to group the categories based on their similarities and differences. Overall, one main category, two subcategories (axial codes), and 18 subcategories were identified.
Findings: The analytical findings indicated that the use of GenAI tools in scientific research creates numerous opportunities as well as challenges. The identified opportunities include enhancing equity; increasing the speed and accuracy of collecting, organizing, and analyzing large volumes of scientific data; facilitating and broadening digital access; improving university services; enhancing the accuracy and quality of academic writing; accelerating scientific peer-review processes; making research more engaging and comprehensible; and enabling new forms of academic writing and research. The findings also revealed several challenges, including algorithmic bias and discrimination; concerns regarding transparency and privacy; the generation of inaccurate information; lack of originality and reliability; insufficient accountability and risks of plagiarism; the accelerated production of low-quality articles; legal concerns related to intellectual property rights and copyright; the risk of users misinterpreting or misunderstanding information; and the potential loss or replacement of jobs in the research sector.
Conclusion: The findings showed that the use of GenAI in scientific research, while creating opportunities to enhance the speed, accuracy, quality, and accessibility of research processes, also entails challenges such as bias, misinformation, threats to academic integrity, legal uncertainties, and reduced transparency and accountability. Therefore, addressing this technology should not be limited to its adoption or restriction, but should instead focus on its responsible governance and use. This requires developing clear policies and guidelines, enhancing AI literacy and research ethics, and fostering cooperation among researchers, universities, policymakers, scholarly publishers, and other stakeholders in the research ecosystem to capitalize on the potential of GenAI while safeguarding academic integrity, credibility, and trust.

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Sciences and Techniques of Information Management
Volume 12, Issue 2
June 2026
Pages 85-103

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