Bibliometric Literature Review: The Adoption of Artificial Intelligence to Improve Organizational Performance and Reduce the Risk of Failure

Abstract

With regard to businesses, the development of new business models and competitive advantages through the integration of artificial intelligence (AI) into management strategies has become a crucial element for their sustainability and competitiveness. However, most companies struggle to seize opportunities for value creation, while others use AI successfully. According to the literature, the performance benefits, success criteria, and challenges related to AI adoption have been highlighted in previous research. The integration of AI has led to significant changes in how companies are managed and how decisions are made, resulting in more efficient and accurate processes and, consequently, improved organizational and overall performance. This study proposes an analysis of the specialized literature in the field of AI to highlight the impact generated by these technologies on business performance. For this study, we selected 478 references from the Web of Science database, published between 2015 and 2025, which were then filtered according to three selection criteria based on timeliness, relevance, and reliability of sources, ultimately retaining 147 articles. The mapping of the scientific literature was carried out using various statistical software tools, namely R-Package, Bibliometrix, Biblioshiny, and VOSviewer.The results of the study highlight a growing trend in the number of publications analyzing the impact of AI technologies on business performance since 2011. Finally, the results revealed a strong link between the concept of artificial intelligence and the fields of management and business administration. Our study contributes to the literature on AI technologies and business performance by highlighting key concepts from previous research, the spatial distribution of publications, and a rapid and in-depth analysis of outstanding scientific articles in the field.

Classification JEL: M21

Paper type: Theoretical Research