Literature Review Using Agentic AI: Work Faster, Stay Rigorous

Key takeaways

• Agentic AI refers to tools that plan and carry out several research steps toward a goal, such as searching for papers, screening results and drafting a structured summary, rather than answering a single prompt.
• In a literature review, an agent works like a research assistant that prepares material, while the researcher sets the question, checks the output and makes the final judgments.
• The tutorial frames agents as a way to reduce the hours spent on repetitive searching and reading work.
• The biggest time savings tend to come from the most repetitive parts of a review, such as initial searching, sorting results and pulling key points from abstracts.
• How much time is actually saved depends on the topic and on how much verification the material needs.
• Reading key papers closely and checking every citation still takes researcher time, and the tutorial stresses that these steps should not be skipped.
• Defining the research question carefully at the start gives the agent a clearer goal and makes its output easier to evaluate.