  The escalating volume of academic literature presents a formidable challenge
in staying updated with the newest research developments. Addressing this, this
study introduces a pioneering AI-based tool, configured specifically to
streamline the efficiency of the article selection phase in Systematic
Literature Reviews (SLRs). Utilizing the robust capabilities of OpenAI's GPT-4
Assistant API, the tool successfully homogenizes the article selection process
across a broad array of academic disciplines. Implemented through a tripartite
approach consisting of data preparation, AI-mediated article assessment, and
structured result presentation, this tool significantly accelerates the
time-consuming task of literature reviews. Importantly, this tool could be
highly beneficial in fields such as management and economics, where the SLR
process involves substantial human judgment. The adoption of a standard GPT
model can substantially reduce potential biases and enhance the speed and
precision of the SLR selection phase. This not only amplifies researcher
productivity and accuracy but also denotes a considerable stride forward in the
way academic research is conducted amidst the surging body of scholarly
publications.
