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Guide to an AI-Driven Literature Review

Prof. Benita OlivierEnglishLiterature reviewStep-by-step AI literature review

TL;DR

1-min read

Searching, filtering, synthesising studies and locating research gaps can make a literature review feel overwhelming, especially the first time. This hands-on tutorial sets out a workflow for building a deep, well-structured review from scratch with SciSpace Agent. It is designed for students writing their first literature review and for experienced researchers who want to streamline a process they already know. The focus is on improving the quality of evidence synthesis rather than only working faster, with AI handling groundwork and the researcher handling interpretation.

Key takeaways

  • A repeatable sequence replaces ad hoc searching: define a focused question, search relevant databases, screen results against clear criteria, extract key information, group findings into themes and write the synthesis.
  • SciSpace Agent supports the early stages by helping you search for and filter relevant studies on your topic.
  • Findings from multiple papers can then be synthesised into a structured, coherent review that highlights agreements and contradictions.
  • Research gaps are identified during the review itself, by noting where open questions in the field remain.
  • Organisation is emphasised at every stage, with notes on each decision so you know what you found and why each source matters, which also makes the review easier to update and defend.
  • AI speeds up searching, summarising and organising, but you still need to read key papers, check summaries for accuracy, verify every citation and decide how findings relate to your question.
Apply it

To apply this, run your focused question through SciSpace's Literature Review Generator and record extracted details for each study in the Literature Review Matrix.

How to do it

  1. Adopt a repeatable review workflow

    Set up a workflow you can repeat for any AI literature review built from scratch. A repeatable process makes your first review less overwhelming.

  2. Search and filter with SciSpace Agent

    Use SciSpace Agent to search for relevant studies and filter them down to what matters. Good filtering saves time in every later step.

  3. Synthesise findings across papers

    Combine findings from multiple papers into a structured, coherent review. Synthesis turns a list of studies into an argument.

  4. Identify research gaps as you go

    Note research gaps while you review the literature rather than at the end. Tracking them early sharpens your final conclusions.

  5. Keep the review organised

    Build habits that keep each stage organised. Staying organised improves the quality of your evidence synthesis.

Watch the tutorial40 min

Guided AI-Driven Literature Review with SciSpace AgentPlay video: Guided AI-Driven Literature Review with SciSpace Agent

Chapters

  1. Welcome and introduction
  2. Can AI write your literature review? AI-assisted vs AI-generated
  3. How to plan a literature review with dedicated time blocks
  4. The sticky-note trick to stop thesis procrastination
  5. Where to find example literature reviews to model
  6. How to write a literature review outline before using AI
  7. How to map a research field with SciSpace Deep Review
  8. Listen, save, cite and export papers to EndNote in SciSpace
  9. How to chat with a research paper using AI
  10. How to find similar papers to your best source with AI
  11. How to read a Deep Review report and its evidence tables
  12. How to draft a literature review outline with SciSpace Agent
  13. What is the purpose of a literature review? It is not a lecture
  14. How long should a literature review be? Writing one section at a time
  15. How to beat writer's block with free writing
  16. Build an evidence table for each section with SciSpace Agent
  17. How to critically appraise studies in a literature review with AI
  18. Final checks: references, Turnitin and accidental plagiarism

Try this on SciSpace

Frequently asked questions

What are the steps of a literature review?

A typical review moves through defining a focused question, searching relevant databases, screening results against clear criteria, extracting key information from each study, grouping findings into themes, and writing a synthesis that highlights agreements, contradictions and gaps. Keeping notes on each decision makes the review easier to update and defend.

Can AI write my literature review for me?

AI can speed up searching, summarising and organising studies, but it should not replace your judgement. You still need to read key papers, check that summaries are accurate, verify every citation and decide how findings relate to your research question. The strongest reviews use AI for groundwork and the researcher for interpretation.

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