Designing an AI-Driven SLR Workflow for Academic Research: A Rubric for Comparative Analysis of AI Tools

Systematic Literature Reviews (SLR) are a critical aspect of academic research, as they provide a comprehensive and rigorous synthesis of existing evidence. However, conducting such reviews presents several challenges that researchers must be aware of to ensure the quality and validity of their work. One of the most significant challenges is developing a clear research question through a comprehensive literature search. This is because it can be difficult to identify appropriate and relevant studies. Additionally, the traditional literature review process has the potential for bias. To address these challenges, researchers need a search protocol and strategy that includes a set of available artificial intelligence-based tools as an ad-hoc tech stack (workflow) to conduct SLR. This study evaluated a proposed model of a workflow and stack of such tools using a rubric to identify the best possible set of tools for the task. For one-year, several AI-based tools were evaluated in two phases, and a proposed workflow using the best of those tools was identified. Sixty-three students used the proposed model to conduct their academic research. The results showed that it is possible to perform academic research more efficiently if a workflow is used for performing SLR.