Finding relevant literature in scientific research is both fundamental and challenging, especially with the surge in publications. Traditional search methods often yield incomplete results, but the rise of artificial intelligence (AI) is transforming this process. This paper examines how AI tools enhance the efficiency and accuracy of literature searches through advanced techniques. This systematic literature review (SLR) utilizes papers from the Web of Science database to highlight key trends and authors at the intersection of AI and scientific research. For this purpose, documents within the Web of Science scientific database were used to gather information on the research topic showing the main trends, findings, affiliations, and authors that focused on the intersection of AI tools in scientific literature search. This article conducts a comprehensive bibliometric analysis of 398 articles dealing with the application of AI tools in scientific issues in the period 2021–2025, with the application of the keywords “AI tools” and “Scientific literature Search” The findings suggest that AI-driven tools streamline study identification and mitigate the limitations of traditional methods. Despite challenges like data bias and interpretability, the review highlights AI's potential to revolutionize literature research, leading to deeper insights and more impactful scientific contributions.
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