If you’ve ever done a systematic literature review (SLR) or a meta-analysis, you know how overwhelming it can feel: endless papers, screening abstracts for hours, extracting data by hand, and then trying to piece everything together.
The good news? AI tools can take a lot of that pain away. While they won’t (and shouldn’t) replace human judgment, they can save you weeks of work and make the whole process smoother.
Here are five of the best AI-powered tools you can start using today:
1. Elicit – Your All-in-One Review Assistant
Elicit is like having a research assistant that never sleeps. It can:
- Search through 125+ million papers (PubMed, arXiv, BMJ, and more).
- Suggest inclusion/exclusion criteria.
- Extract numbers, tables, and quotes with >90% accuracy.
- Even draft a first version of your results summary.
Why use it? It’s one of the only tools that covers multiple stages of the review—search, screen, extract, and report.
2. Rayyan – Speed Up Screening by 90%
Rayyan is a favorite among researchers because it makes the title and abstract screening phase so much faster.
With Rayyan, you can:
- Use AI to predict which studies are relevant.
- Deduplicate papers automatically.
- Apply PICO criteria and generate PRISMA flow diagrams.
- Work on your laptop or phone with its mobile app.
Why use it? If your main bottleneck is screening papers, this is the tool for you.
3. RobotReviewer + Abstrackr + EPPI-Reviewer – The Power Combo
These three often work best together:
- RobotReviewer: Checks for risk of bias and extracts data, especially from randomized controlled trials.
- Abstrackr: Uses AI to help screen abstracts quickly, with minimal risk of missing key studies.
- EPPI-Reviewer: A full platform for screening, keyword tagging, extracting data, and even running your meta-analysis.
Why use it? This combo is especially useful if you want automation and transparency, with solid validation from academic studies.
4. SciSpace – Smarter Reading, Faster Insights
SciSpace is like ChatGPT but trained for research papers. It helps you:
- Summarize long papers.
- Explain complex figures or jargon.
- Search across massive open-access databases.
- Ask questions directly inside PDFs.
Why use it? Perfect if you’re drowning in dense papers and need quick, reliable explanations.
5. Semantic Scholar – Find Key Papers Fast
Semantic Scholar uses AI to help you discover and skim papers quickly. It offers:
- “TLDR” one-sentence paper summaries.
- Smart citation cards and highlight suggestions.
- Personalized research feeds that recommend new studies.
Why use it? Great for discovery—helps you decide which papers are worth reading in depth.
Bonus Tools to Explore
Some exciting newer tools are emerging too:
- ASReview: Open-source tool using machine learning to speed up screening.
- LRN (Literature Review Network): An AI pipeline that completed a review in days instead of months.
- AiReview: A large language model (LLM) approach for screening.
- Manalyzer: An experimental multi-agent system aiming to automate entire meta-analyses.
Final Thoughts
Systematic reviews and meta-analyses will probably never be “easy”—but AI is making them much faster, less repetitive, and more accurate.
- If you want end-to-end help, go with Elicit.
- If you need speed in screening, choose Rayyan.
- If you want robust data and bias checking, use RobotReviewer + EPPI-Reviewer.
- If you’re focused on understanding dense papers, try SciSpace.
- For finding the right studies quickly, Semantic Scholar is hard to beat.
