How to Conduct a Literature Review with AI: A Step-by-Step Workflow
Quick answer
A reliable AI-assisted literature review in SciSpace starts with a focused question and a documented search scope. Use SciSpace Literature Review to discover and filter papers, compare them in a consistent evidence matrix, inspect pivotal studies with Chat with PDF, and synthesize themes, disagreements, and gaps. Treat AI summaries as navigation aids and verify every important claim against the original paper.
About this video
This tutorial demonstrates how to use the SciSpace literature review tool, focusing on its three distinct output modes: standard, high quality, and deep review. The session highlights workflows for extracting information into tables, customizing instructions for specific data points, and verifying cited papers by hovering over provided source links [L5-L12].
A useful literature review does more than collect papers: it maps what is known, where studies disagree, and what remains unanswered. This tutorial demonstrates how SciSpace supports discovery, comparison, deep reading, and thematic synthesis without replacing the researcher’s judgment.
What this tutorial covers
- Translate a research topic into searchable concepts, synonyms, and filters.
- Find relevant papers and compare study design, sample, variables, findings, and limitations.
- Move from paper-by-paper summaries to themes, contradictions, trends, and research gaps.
- Combine agentic and non-agentic tools depending on how much control the task requires.
Key concepts explained
- Search strategy
- A transparent combination of concepts, keywords, filters, and source coverage.
- Evidence matrix
- A structured table that makes studies comparable across shared variables.
- Synthesis
- Integrating patterns across studies rather than concatenating individual summaries.
- Gap identification
- Locating missing populations, methods, settings, measurements, or unresolved contradictions.
How to try it in SciSpace
- 1
Define a focused review question and identify its main concepts and synonyms.
Write a short review protocol before searching. Record the question, main concepts, population or context, date range, evidence types, inclusion boundaries, and the decision the review should support.
- 2
Search in Literature Review, apply relevant filters, and save promising studies.
Save the exact query, databases or sources, filters, search date, and result count. Check a sample of relevant and irrelevant records to identify missing synonyms or overly broad terms.
- 3
Create custom comparison columns for methods, sample, outcomes, main findings, and limitations.
Define each evidence-matrix column before extraction and pilot it on five papers. Use consistent fields for design, sample, intervention or exposure, outcome, finding, limitation, and evidence location.
- 4
Read the most important papers with Chat with PDF and verify the extracted evidence.
Open pivotal and methodologically complex papers in full. Compare AI-extracted details with the methods, tables, and results sections, and retain page or passage references for important fields.
- 5
Ask SciSpace to synthesize the table by theme, agreement, disagreement, trend, and research gap.
Synthesize across studies rather than writing one summary per paper. Link every theme, disagreement, trend, and proposed gap to the studies that support, qualify, or contradict it.
Worked example
A researcher asks: among university students, how is sleep duration associated with academic performance? In SciSpace Literature Review, they search empirical studies from 2018 onward and compare design, sample, sleep measure, academic outcome, and confounders. The matrix reveals that cross-sectional studies often rely on self-reported sleep, while the few longitudinal studies use different academic measures. The researcher opens the strongest papers in Chat with PDF, verifies the relevant passages, and writes a synthesis that explains why the findings differ instead of claiming a single universal effect.
Practice prompt
Find peer-reviewed research on [topic] from [years]. Compare study design, population, sample size, measures, findings, and limitations. Group the evidence into themes, identify contradictions, and propose research gaps supported by the included studies.
Key takeaway
The quality of an AI-assisted literature review depends on a clear question, a transparent evidence table, and synthesis that can be traced back to the original papers.
Frequently asked questions
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