Literature reviews have long been a cornerstone of academic writing, enabling scholars to identify gaps, trace theoretical developments, and position their work within a field. But with the rise of AI tools—from ChatGPT to Elicit to Semantic Scholar’s AI assistant—the process of reviewing literature is rapidly evolving.

When used responsibly, AI can enhance both the efficiency and depth of a literature review. However, if misused, it risks undermining scholarly rigor and academic integrity.

This article provides best practices for utilizing AI in literature reviews, integrating technological support with critical thinking and ethical considerations.

Why Use AI for Literature Reviews?

AI tools can assist in multiple aspects of the literature review process:

Search optimization: Finding relevant studies more quickly

Summarization: Condensing long articles into key points

Classification: Grouping papers by theme or methodology

Citation assistance: Suggesting sources based on your topic

But convenience comes with caveats: not all tools are accurate, and AI cannot replace human analysis or academic judgment.

Key AI Tools for Literature Review Support

Tool	Main Use	Strength	Limitation
ChatGPT	Brainstorming, paraphrasing, summarizing	Flexible language generation	May hallucinate sources or data
Elicit.org	Semantic paper search, extracting findings	AI-powered extraction from real papers	Limited database; misses niche fields
Scite.ai	Evidence-based citation analysis	Contextual citation classification	Focused on STEM research
Semantic Scholar	Paper discovery and citation graphs	Academic-focused with AI filtering	Less comprehensive than Google Scholar
Research Rabbit	Visualizing research networks	Interactive mapping of literature	Steep learning curve

Best Practices for Integrating AI into Literature Reviews

1. Start with a Human-Curated Query

Before prompting AI, define your research question, scope, and keywords manually. This ensures:

• Greater relevance of retrieved sources
• Fewer irrelevant or broad suggestions
• Better control over the review direction

AI tools perform optimally when provided with structured input. Don’t rely on vague prompts like “Find me recent papers on climate policy.”

2. Verify Every Source

AI tools might generate fake citations, pull outdated references, or misattribute authors. Always verify:

• The existence of a source (via Google Scholar, Crossref)
• The accuracy of metadata (authors, dates, journal)
• Whether the findings match what the AI claims

🔍 Tip: When using ChatGPT or Elicit, cross-reference AI-suggested papers with real databases.

3. Use AI to Summarize, Not Analyze

AI tools can provide quick summaries, but they cannot evaluate theoretical contributions or compare methodologies with the scholarly nuance required. Use AI to:

• Identify main findings
• Extract methodologies
• Locate keywords or cited studies

But always follow with a human interpretation of relevance and quality.

4. Keep a Transparent Workflow

Document which parts of your review were AI-assisted. This can include:

• Tools used
• Prompts or queries entered
• Any limitations or concerns

Such transparency improves research integrity and aligns with emerging academic guidelines.

Ethical Considerations and Risks

Using AI in research requires not only technical skill but also ethical awareness.

Key risks include:

Plagiarism: Copying AI-generated summaries without attribution

Bias amplification: AI may surface only dominant perspectives, excluding marginalized voices

Over-reliance: Losing critical engagement with the literature

Risk	Impact	Best Practice
Fake citations	Compromises academic credibility	Always validate with real databases
Misleading summaries	Skews understanding of study findings	Read abstracts or full papers
Unattributed AI use	Violates academic honesty policies	Disclose AI support in your methods

When (and When Not) to Use AI

Use AI When:

• Exploring a new research area and need a quick overview
• Sorting large volumes of papers
• Extracting methods or metrics across studies
• Brainstorming keywords or gaps

Avoid AI When:

• Writing the final synthesis or theoretical framing
• Concluding limited data
• Performing a critical evaluation of literature
• Submitting unverified references

Tips for Educators and Supervisors

• Set clear policies on how students can use AI tools
• Discuss limitations openly in seminars and labs
• Design assignments that require personal reflection and analysis
• Encourage annotated bibliographies with reasoning for source inclusion

“AI can be a co-pilot in research, but the student must remain the pilot.”

Augment, Don’t Replace

Artificial intelligence (AI) offers tremendous promise for navigating scholarly literature. It can accelerate discovery, improve organization, and reduce information overload. But it cannot—and should not—replace critical thinking, source validation, or academic judgment.

Used wisely, AI becomes a valuable assistant, not a shortcut. As we enter the next chapter of academic research, let’s teach students and scholars to use these tools ethically, skillfully, and transparently.