Scientometric Analysis of Artificial Intelligence in the Digital Economy

DOI

10.2991/978-94-6239-699-9_7How to use a DOI?

Keywords

artificial intelligence; Internet economy; scientific econometric analysis; Interactive customer service

Abstract

As the digital economy enters a period of deepening applications, artificial intelligence has become an important tool for reshaping the economic structure. Based on the Web of Science core collection database, this paper conducts a systematic scientiometric analysis of 494 papers in the field of artificial intelligence in the digital economy. By constructing keyword co-occurrence networks and clustering maps, this study reveals the evolution context and frontier hotspots of this field. The results show that: (1) The research hotspots focus on “AI-empowered green ESG”, “labor market reconstruction”, and “data element governance”, indicating that AI research is transforming from a simple technical efficiency orientation to a sustainable development and social governance orientation. (2) The time series map shows that the focus of research has shifted from the early “technical architecture construction” (such as cloud computing and Internet of Things) to the in-depth “scenario-based empowerment” (such as generative AI, metaverse, digital finance). (3) “Interactive AI”, “algorithm compliance,” and “cost optimization and efficiency enhancement” are the most promising research directions at present. This study objectively presents the knowledge structure of AI research in the digital economy, and also provides a scientific basis for understanding the economic externalities of AI technology.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Lv-Xun Lan
AU  - Hao-Ming Huang
AU  - Chunglien Pan
PY  - 2026
DA  - 2026/06/02
TI  - Scientometric Analysis of Artificial Intelligence in the Digital Economy
BT  - Proceedings of the 2026 4th International Conference on Digital Economy and Management Science (CDEMS 2026)
PB  - Atlantis Press
SP  - 48
EP  - 56
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-699-9_7
DO  - 10.2991/978-94-6239-699-9_7
ID  - Lan2026
ER  -