Systematic analysis of generative AI tools integration in academic research and peer review
Hussain Salman, Muhammad Aliif Ahmad, Roliana Ibrahim, Jamilah Mahmood
Abstract
While sparking a big debate among academics, generative artificial intelligence (GAI) tools are becoming integral to academic research, holding the potential to transform traditional research and peer review methods. This systematic literature review investigates the emergent role of GAI tools in academic research workflow and scholarly publications by analyzing 44 articles. The process of identifying the most relevant publications was done following the preferred reporting items for systematic reviews and meta-analyses method. The findings provide a thorough understanding of how GAI is currently being utilized in the various aspects of academic research workflow and peer review process, including concerns, limitations, and proactive measures to better employ these tools effectively. Our review suggests the need for more research to develop appropriate policies and guidelines, enhance researchers’ artificial intelligence literacy through targeted training, and ensure ethical use of these tools to boost research productivity and quality.