Recently developed AI research tools can be used to identify resources on a topic, or identify resources that are similar, or linked in some way, to already identified sources. When deciding whether or not to use these tools it's important to:

• Check with your supervisor or lecturer as to whether or not it is allowed and/or appropriate to use these tools for your literature review or assessment.
• Read Your guide to generative AI.
• Keep in mind that these tools have limitations and biases.
• Use these tools with transparency.
• Always evaluate the quality of any information you have found.

Tips:

• Use these tools in conjunction with other search tools, such as journal databases, library catalogues, and citation databases.
• Check out the Library's Generative AI at University: For Research Guide for more advice on using AI tools ethically and responsibly.
• A great starting point is Primo's AI Research Assistant which will link to resources in the Library's catalogue. 

Read:

Some examples of AI research tools are listed below:

Please Note: Examples below are not recommendations but are provided for your information. Please use with care and evaluate all resources found via these tools. 

ResearchRabbit

• A citation-based literature mapping tool.
• Add relevant seed papers to a collection to receive recommendations for related, or connected, papers.
• Simple keyword search function also provided.
• Free to use, login with a free account.

Semantic Scholar

• AI-powered academic search and discovery tool.
• AI algorithms assist in discovering hidden connections and links between research topics.
• New Semantic Reader application contextualises citations and improves accessibility among other features. 
• Free to use, login with a free account.

Elicit

• AI tool that finds articles, summarises abstracts and extracts key information from the article.
• Searches across 200 million academic papers from Semantic Scholar.
• Helps brainstorm your research question.
• Useful to find seed papers for your literature review or to check if you have missed anything after searching the databases.
• Pay-as-you-go service once free trial credits have been used.

Connected Papers

• Creates a graph that maps literature related to an inputted paper.
• Input using an existing article, or conduct a topic search to locate an article.
• Search engine is powered by Semantic Scholar.
• Free tier (offering 5 graphs per month) available.

Journal Articles

Bernard, N., Sagawa Jr, Y., Bier, N., Lihoreau, T., Pazart, L., & Tannou, T. (2025). Using artificial intelligence for systematic review: The example of elicit. BMC Medical Research Methodology, 25(1), 75.  https://doi.org/10.1186/s12874-025-02528-y 

Clark, J., Barton, B., Albarqouni, L., Byambasuren, O., Jowsey, T., Keogh, J., Liang, T., Moro, C., O’Neill, H., & Jones, M. (2025). Generative artificial intelligence use in evidence synthesis: A systematic review. Research Synthesis Methods, 16(4), 601-619.  https://doi.org/10.1017/rsm.2025.16  

Eacersall, D., Pretorius, L., Smirnov, I., Spray, E., Illingworth, S., Chugh, R., Strydom, S., Stratton-Maher, D., Simmons, J., Jennings, I., Roux, R., Kamrowski, R., Downie, A., Thong, C. L., & Howell, K. A. (2024). Navigating ethical challenges in generative AI-enhanced research: The ETHICAL framework for responsible generative AI use. ArXiv Preprint, 1-29. https://arxiv.org/abs/2501.09021   

Fabiano, N., Gupta, A., Bhambra, N., Luu, B., Wong, S., Maaz, M., Fiedorowicz, J. G., Smith, A. L., & Solmi, M. (2024). How to optimize the systematic review process using AI tools. JCPP Advances, 4(2), e12234.  https://doi.org/10.1002/jcv2.12234 

Gartlehner, G., Kahwati, L., Hilscher, R., Thomas, I., Kugley, S., Crotty, K., Viswanathan, M., Nussbaumer-Streit, B., Booth, G., Erskine, N., Konet, A., & Chew, R. (2024). Data extraction for evidence synthesis using a large language model: A proof-of-concept study. Research synthesis methods, 15(4), 576–589. https://doi.org/10.1002/jrsm.1710

Ge, L., Agrawal, R., Singer, M., Kannapiran, P., De Castro Molina, J. A., Teow, K. L., Yap, C. W., & Abisheganaden, J. A. (2024). Leveraging artificial intelligence to enhance systematic reviews in health research: Advanced tools and challenges. Systematic Reviews, 13(1), 269.  https://doi.org/10.1186/s13643-024-02682-2  

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