SciSpace Academy

How to Do a Literature Review with AI

Taught by Dr. Ryan Chou, Prof. Benita Olivier +29 experts

31experts66tutorials11languages

A literature review is where most research projects either gain direction or stall.

  • Build a search strategy and find the right papers fast
  • Organise evidence in a comparison table and verify claims in the full text
  • Write a synthesis organised by theme, not paper by paper

Try this on SciSpace

Showing 66 tutorials

Step-by-step AI literature review

Go from a research question to a written synthesis: build a search strategy, screen papers, compare findings and write up themes, with every claim checked against the full text.

Find research papers with AI

Search beyond keyword matching: turn your question into a search strategy, surface relevant papers Google Scholar misses and narrow a long list down to the studies that matter.

Read and understand papers

Ask questions of a PDF, decode methods and statistics, and read critically, so you understand a paper before you cite it.

Extract data and build a literature matrix

Pull the same fields from every paper into an evidence table, map theories and constructs, and turn the table into a synthesis organised by theme.

Find research gaps and new ideas

Use the literature to spot what has not been studied yet, test whether a gap is real and turn it into a novel, defensible research question.

Manage literature overload and references

Triage a growing reading list, organise papers in a library and keep Zotero or Mendeley in sync, so nothing important gets lost.

End-to-end research workflow with AI agents

Follow one project from literature search to submission with SciSpace Agent: search, review, analysis and drafting in a single, checkable workflow.

Responsible and ethical AI literature reviews

Know what to delegate to AI and what must stay with you: verify sources, avoid fabricated citations and keep the judgement that evidence synthesis needs.

Literature reviews for health and biomedical research

Find, interpret and evaluate clinical and biomedical studies with AI, with the extra care that health evidence demands.

Learning path

Beginner to intermediate · 5 lessonsLiterature Review with AI in 5 LessonsGo from a research question to a written synthesis. You will build a search strategy, organise papers in an evidence table, verify claims in the full text and manage literature overload.

About this use case

A literature review is where most research projects either gain direction or stall. You need to find the right papers, read far more than you have time for, and turn scattered findings into an argument. AI can speed up every one of those steps, but only if you keep control of the question, the sources and the synthesis.

This hub collects every SciSpace Academy tutorial on literature reviews. You will learn how to build a search strategy, screen and organise papers, extract findings into a comparison table, check claims against the full text with Chat with PDF, and write a synthesis that is organised by theme rather than paper by paper. Tutorials are led by researchers, librarians and SciSpace specialists, and many are available in Portuguese, Spanish, Thai, Chinese, Turkish, Indonesian and other languages.

Frequently asked questions

Can AI write my literature review for me?

AI can help you find papers, summarise them and organise evidence, but the research question, judgement about study quality and the final argument must be yours. Use AI outputs as a starting point, verify every claim against the original paper and disclose AI use according to your institution's or journal's policy.

How many papers should a literature review include?

There is no fixed number. It depends on your field, the scope of the question and the type of review. A focused thesis chapter may synthesise 30 to 60 sources, while a systematic review reports every study that meets its inclusion criteria. Prioritise relevance and quality over volume.