A literature review means finding the important research on your topic, reading it, and explaining how the studies connect — where they agree, where they disagree and what's missing. AI research tools can speed up searching, screening and organizing papers, but they can miss studies, misread findings and even invent citations. This guide shows a workflow that keeps you in charge and compares the tools that help.
Check your course's AI policy before using AI on a graded literature review. AI can help you find and organize papers, but the synthesis — how studies relate and what gaps remain — is what you're graded on. Read every paper you cite, check each citation against the original, and follow your instructor's rules on AI use and disclosure.
Write a focused research question and decide your limits — date range, study types, populations or disciplines — before you search.
Use Elicit or Consensus to find relevant papers quickly, then run the same search in your library databases or Google Scholar so you don't miss key studies.
Skim titles and abstracts, keep the relevant papers and save each one to Zotero so your citations stay accurate from the start.
Read the papers and note each study's question, method, sample and findings. AI summaries and extraction tables can help you compare studies, but check every detail against the paper.
Organize your sources by theme, method or debate rather than summarizing one paper after another. Tools like Gemini Notebook can help you search across your uploaded papers.
Explain how the studies connect, where they disagree and what gaps remain, in your own words. If your instructor allows AI help, use it to react to your outline, not to write the review.
Insert citations with Zotero in your required style, confirm every source exists and says what you claim, and proofread before you submit.
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