Application of Artificial Intelligence in Aerospace Engineering and Its Future Directions: A Systematic Quantitative Literature Review

Abstract

This research aims to comprehensively analyze the most essential uses of artificial intelligence in Aerospace Engineering. We obtained papers initially published in academic journals using a Systematic Quantitative Literature Review (SQLR) methodology. We then used bibliometric methods to examine these articles, including keyword co-occurrences and bibliographic coupling. The findings enable us to provide an up-to-date sketch of the available literature, which is then incorporated into an interpretive framework that enables AI's significant antecedents and effects to be disentangled within the context of innovation. We highlight technological, security, and economic factors as antecedents prompting companies to adopt AI to innovate. As essential outcomes of the deployment of AI, in addition to identifying the disciplinary focuses, we also identify business organizations' product innovation, process innovation, aerospace business model innovation, and national security issues. We provide research recommendations for additional examination in connection to various forms of innovation, drawing on the most critical findings from this study.