This manuscript presents a comprehensive review of the use of Artificial Intelligence (AI) in Systematic Literature Reviews (SLRs). A SLR is a rigorous and organised methodology that assesses and integrates previous research on a given topic. Numerous tools have been developed to assist and partially automate the SLR process. The increasing role of AI in this field shows great potential in providing more effective support for researchers, moving towards the semi-automatic creation of literature reviews. Our study focuses on how AI techniques are applied in the semi-automation of SLRs, specifically in the screening and extraction phases. We examine 21 leading SLR tools using a framework that combines 23 traditional features with 11 AI features. We also analyse 11 recent tools that leverage large language models for searching the literature and assisting academic writing. Finally, the paper discusses current trends in the field, outlines key research challenges, and suggests directions for future research.

翻译：本文系统综述了人工智能在系统性文献综述中的应用。系统性文献综述是一种严谨且规范化的研究方法论，用于评估和整合某个研究主题的已有成果。目前已开发出多种工具以辅助并部分自动化系统性文献综述流程。人工智能在该领域日益增长的作用展现出为研究者提供更高效支持的巨大潜力，推动文献综述向半自动生成方向发展。本研究重点探讨人工智能技术如何应用于系统性文献综述的半自动化过程，特别是筛选与提取阶段。我们采用融合23项传统特征与11项人工智能特征的分析框架，对21款主流系统性文献综述工具进行评估，同时分析了11款利用大语言模型进行文献检索与学术写作辅助的新型工具。最后，本文探讨了该领域的发展趋势，概述了关键研究挑战，并提出了未来研究方向。