Can AI tools help automate the writing of literature reviews?

Yes, AI tools can significantly assist in automating parts of the literature review process. They are feasible for accelerating various stages of information gathering and initial synthesis. These tools primarily leverage natural language processing (NLP) to analyze vast volumes of text, identifying key themes, methodologies, gaps, and citation patterns within relevant academic literature. Their effective application necessitates high-quality input data, clear research questions, and iterative refinement of AI queries. Crucially, human expertise remains indispensable for evaluating content quality, relevance, methodological rigor, and theoretical coherence; AI serves as an augmentative tool, not a replacement. Responsible use requires careful fact-checking of AI outputs and adherence to academic integrity standards regarding content generation. In practice, AI assists by efficiently scanning databases, summarizing articles, drafting preliminary topic overviews, suggesting connections between studies, and generating initial drafts of specific sections. This automation dramatically improves scalability and efficiency, freeing researchers' time for higher-level critical analysis, interpretation, and synthesis. Ultimately, AI enhances productivity by handling labor-intensive initial tasks, while the researcher maintains oversight and deep intellectual contribution to the review.