Author
Listed:
- Maurício Benedeti Rosa
- Luis Claudio Kubota
Abstract
Purpose Artificial Intelligence (AI) has the potential to significantly increase long-term economic productivity. Although available evidence indicates that the use of AI in major business processes is still quite limited, countries such as China and the USA are at the forefront of technology development. For developing economies not to lag behind, it is essential to be prepared through innovation-friendly public policies, which can be more efficiently formulated with an understanding of the factors influencing the adoption of AI by firms. This research paper aims to contribute to this objective by providing a brief characterization of the scientific literature on AI in Brazil and worldwide, and by evaluating the determinants of AI adoption by Brazilian companies.Design/methodology/approach We use a bibliometric tool developed by the OECD to characterize AI research, and parametric modeling – logit, in RStudio, to evaluate the determinants of AI adoption in Brazilian firms.Findings The results that emerge from the analysis point out that Brazil's scientific production on AI is much lower than that of the leading experts, but the rates of AI adoption by companies are in line with those of European countries. As the main technical determinants of AI adoption in Brazilian companies, the use of the internet of things (IoT), cloud computing, big data analysis and the existence of a digital security policy stand out, which reinforces the need to harmonize the different government strategies related to digital transformation in Brazil.Originality/value As far as we are concerned, this is the first attempt to conduct this kind of analysis in Brazil, with Information and Communications Technology (ICT) Enterprises Survey 2021 data.
Suggested Citation
Maurício Benedeti Rosa & Luis Claudio Kubota, 2025.
"Artificial intelligence: where does Brazil stand in global scientific production and what are the main technical determinants of adoption by Brazilian companies,"
EconomiA, Emerald Group Publishing Limited, vol. 26(3), pages 358-374, March.
Handle:
RePEc:eme:econpp:econ-01-2025-0010
DOI: 10.1108/ECON-01-2025-0010
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