Integrating AI-powered academic databases in research methodology

Kudzayi Savious Tarisayi

Chapter 7 in Artificial Intelligence in Postgraduate Research Methodology, 2026, pp 136-153 from Edward Elgar Publishing

Abstract: This chapter explores the integration of AI-powered academic databases in modern research, highlighting their role in enhancing literature discovery, data synthesis, and knowledge mapping. Focusing on Dimensions.ai, Semantic Scholar, and SearchSmart.org, it analyzes their algorithms, semantic search functions, and user interfaces. Through comparative analysis, the chapter demonstrates how these tools improve research efficiency and depth by enabling precise navigation of extensive academic corpora. It also addresses ethical concerns such as algorithmic bias, data privacy, and dependence on automation. By combining theoretical perspectives from information science and AI with practical evaluation, the chapter advances the discourse on AI-augmented research, promoting critical and informed use of these technologies. Ultimately, it offers scholars insights into leveraging AI databases to strengthen research rigor and innovation across disciplines.

Keywords: AI-powered academic databases; Research methodology; Dimensions; Ai; Semantic Scholar; SearchSmart; Org; Semantic search; Ethical considerations in AI (search for similar items in EconPapers)
Date: 2026
ISBN: 9781049408323
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