Abstract
•Comprehensive analysis of 404 articles collected through Web of Science and Scopus databases.•A Text-mining approach based on Latent Dirichlet Allocation (LDA) reveals 18 latent topics.•Citation analysis shows the top citations on Artificial Intelligence in Business category.•Future trends are Robots and Automated Systems, BCI and DBS, Integrated IoT and AI and Law and Ethics.•Future trends examples and implications for society are discussed in the paper.•Research Questions for future research are proposed regarding the future trends.
This study provides an overview of state-of-the-art research on Artificial Intelligence in the business context and proposes an agenda for future research. First, by analyzing 404 relevant articles collected through Web of Science and Scopus, this article presents the evolution of research on AI in business over time, highlighting seminal works in the field, and the leading publication venues. Next, using a text-mining approach based on Latent Dirichlet Allocation, latent topics were extracted from the literature and comprehensively analyzed. The findings reveal 18 topics classified into four main clusters: societal impact of AI, organizational impact of AI, AI systems, and AI methodologies. This study then presents several main developmental trends and the resulting challenges, including robots and automated systems, Internet-of-Things and AI integration, law, and ethics, among others. Finally, a research agenda is proposed to guide the directions of future AI research in business addressing the identified trends and challenges.