A Bibliometric Analysis of Research Trends in AI Integration within Cloud Computing

Mega Fitri Yani; Istifa Shania Putri; Cindy Muhdiantini; Farid Munadhil

doi:10.5281/zenodo.19927559

Authors

Mega Fitri Yani Telkom University, Indonesia Author
Istifa Shania Putri Telkom University, Indonesia Author
Cindy Muhdiantini Telkom University, Indonesia Author
Farid Munadhil Telkom University, Indonesia Author

DOI:

https://doi.org/10.5281/zenodo.19927559

Keywords:

Artificial Intelligence, Cloud Computing, Bibliometric Analysis, Research Trends

Abstract

The integration of Artificial Intelligence (AI) and cloud computing has emerged as a rapidly expanding research area, driven by the need for scalable, elastic, and cost-efficient intelligent systems. Cloud infrastructures enable dynamic resource allocation and pay-as-you-go models, making them ideal environments for AI model training and deployment. Despite the growing volume of publications, a structured mapping of the intellectual landscape of AI–cloud integration remains necessary. This study aims to analyze the research landscape of AI integration in cloud computing using a bibliometric approach. Data were collected from the Scopus database for the period 2021-2026 using the query “Artificial Intelligence” AND “Cloud Computing”, focusing on English-language articles. The analysis was conducted using the Bibliometrix package in R to examine Annual Scientific Production, Countries Collaboration World Map, Most Relevant Affiliations, Co-occurrence Network, Thematic Map, Most Relevant Words, Trend Topics. The findings reveal a significant increase in publications after 2021, indicating accelerating academic interest in AI–cloud convergence. International collaboration is dominated by countries such as India, China, Saudi Arabia, the United States, and the United Kingdom. Thematic analysis shows that artificial intelligence and cloud computing function as foundational themes, with machine learning acting as a key driving force. Emerging topics such as edge computing and real-time systems suggest a shift toward intelligent, distributed, and data-intensive cloud environments.

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