As AI continues to revolutionize academic research, librarians must stay informed about the latest AI-powered tools and their potential applications. This article explores a range of cutting-edge AI research tools, evaluating their key features, benefits, and drawbacks using the REACT framework (Relevancy, Ease of Use, Assessing DEIA [diversity, equity, inclusion, and accessibility], Currency, Transparency & Accuracy). We focus on two categories of tools: citation-based literature mapping tools and text-extraction tools for literature reviews. The citation mapping tools are Litmaps, Connected Papers, and ResearchRabbit, which help researchers discover and visualize related academic literature. The text-extraction tools—Elicit, scite, and Consensus—assist in finding, summarizing, and analyzing relevant papers.
The Generative AI Product Tracker lists generative AI products that are either marketed specifically towards postsecondary faculty or students or appear to be actively in use by postsecondary faculty or students for teaching, learning, or research activities. The Tracker is a living document, which we update regularly as new products enter the market or new information about existing products becomes available. For more information, see our issue brief, Generative AI in Higher Ed: The Product Landscape. Thanks to Gary Price of Library Journal’s infoDOCKET for invaluable help keeping track of new product releases.
This list is far from comprehensive. Note that all of the tools mentioned here are for individual use; Emory does not subscribe to or endorse any of these tools at this time. The Libraries have been receiving a good number of inquiries as to new tools being added to some of our most popular databases, including Web of Science, Embase, and Reaxys along with campus-wide subscriptions to common tools such as Scite.AI and Consensus. We are working on a number of policies and criteria (Spring 2026) for vetting these.