Artificial Intelligence in Literature Review Synthesis: A Step-by-Step Methodological Approach for Researchers and Academics
Matolwandile Mzuvukile Mtotywa, Jeri-Lee Mowers, Wavhudi Ndou, Thabang V. Q. Moleko, Matsobane Ledwaba
Abstract
The integration of artificial intelligence (AI) in literature reviews aims to transform research by potentially automating processes, enhancing rigour, and improving quality. The study proposes a structured step-by-step approach to integrate AI tools into the literature review synthesis process. The developed methodological approach has five steps. The first step, planning and readiness, involves scoping, understanding practices, and defining boundaries of AI use. Next is selecting AI tools and aligning their capabilities with the literature needs through a matrix. The third step focuses on using AI to conduct the review, followed by validation and cross-referencing of AI-generated results. The final step is disclosing AI use in line with ethical and reporting standards. The approach is demonstrated through five scenarios: emerging or fragmented literature, large or saturated fields, interdisciplinary domains, methodologically diverse studies, and under-researched topics. This approach is designed to enhance transparency, potentially reduce bias, and support reproducibility by aligning AI functions with research goals. It also addresses ethical considerations and promotes human–AI collaboration. For researchers and academics, it aims to provide a practical roadmap for the responsible adoption of AI in literature reviews, supporting efficiency, ethical tool use, transparency, and the balance between machine assistance and academic judgment.