Among the companies that used AI, the areas of administration (73.8%), product project development (65.9%), processes, services and marketing (65.1%) were those that used it the most, followed by the areas of production (56.4%) and logistics (48.4%).[1]
Current scenario
Adoption in Brazilian industrial sectors
Tasks where a significant proportion of companies are using AI, in 2023.
In senior management, the majority (56%) of executives have a long-term vision for its use. The study also shows that IT, Innovation, and Marketing are the areas where AI use is most widespread, and that 43% of companies are developing or adapting the algorithms they use.[2]
The majority of large institutions that reported some type of AI use purchased these solutions from other companies (76%).[3]
Some factors for the adoption of artificial intelligence in companies include the establishment of an autonomous strategy by the company (87.0%), and the influence of suppliers and/or customers (63.0%) and the main difficulties in using technologies were high costs (80.8%), lack of qualified personnel in the company (54.6%) and excessive economic risks (49.5%).[1]
Three variables are considered the most relevant to explain the option to use AI: the implementation of a digital security policy, the size of companies with 250 or more employees and the characteristics of the company related to information and communication.[4]
When analyzing AI use by company size in Brazil, large companies have the highest proportion of AI use, mainly due to their investment capacity and technology experimentation. However, when comparing Brazil and Europe, indicators show an acceleration in AI use among large European companies, while in Brazil the situation remains stable. In 2023, 30% of large companies in the European bloc used some type of AI, a figure that rose to 41% in 2024, while in Brazil these proportions were 41% in 2023 and 38% in 2024.[5]
Workforce
The challenge of upskilling begins with employees who are capable of understanding recent technological changes. Similarly, companies must create the environment and conditions for workforce development conducive to innovation, and universities must be prepared to provide knowledge aligned with the transition process, which in turn must be supported by public policies.[6]
The concern with training a specialized workforce in AI can be seen in the low number of graduates and PhDs in computer science and computer engineering in Brazil, compared to the number shown in other countries.[7]
As recorded in the document Recommendations for the Advancement of Artificial Intelligence in Brazil, 2019 data from the Coordination for the Improvement of Higher Education Personnel (CAPES) indicate that "the number of PhDs graduated annually in computing remained below 400 in 2016, and is not expected to have increased during the Covid-19 pandemic" (ABC, 2023). In the United States, by contrast, the number of PhDs graduated in these two areas has remained around 1,800 for the past 11 years, and during this period, the number of PhDs specializing in AI jumped from 10% to 19%.[7]
Based on data from the CNPq Lattes Platform (October 2019), it is possible to observe that the number of professionals in the AI field in Brazil is 4,429 specialists. This is still a small number compared to the 415,166 IT jobs in the country's business sector alone.[8]
R&D, scientific production and integration with industry
Regarding the promotion of research and technologies related to AI, public entities such as the Coordination for the Improvement of Higher Education Personnel (Capes) and the National Council for Scientific and Technological Development (CNPq) stood out as the main funders.[4]
Currently, different countries and territories have been promoting the development of Artificial Intelligence (AI). In the Brazilian case, one of the main initiatives is the creation of Engineering Research Centers/Applied Research Centers (CPE/CPA) in AI by the São Paulo Research Foundation (FAPESP), in collaboration with the Ministry of Science, Technology and Innovation (MCTI), the Ministry of Communications (MC) and the Brazilian Internet Steering Committee (CGI.br).[7]
The US is home to approximately 60% of the world's top AI researchers, followed by China (11%), Europe (10%), and Canada (6%).[10]
To change this scenario, in August 2024, the Brazilian government announced an investment of R$23 billion until 2028 in artificial intelligence, seeking to “transform the country into a global reference in innovation”.[3]
Future challenges
Ursula von der Leyen speaking during the Artificial Intelligence Action Summit at the Grand Palais, in Paris, 2025.
The Organization for Economic Cooperation and Development (2020) report highlighted three factors that hinder the digital transformation journey and application of AI in Brazil: insufficient infrastructure, high costs due to the tax system, and financial limitations, such as limited access to financing.[11]
The costs of adopting technology, its incompatibility with the business, and the lack of training also represent obstacles that Brazilian industry must overcome.[3]
There are also inherent obstacles for companies. A McKinsey review emphasizes that once a company chooses one or more sectors to focus on, it must select specific applications. Buyers aren't interested in artificial intelligence simply because it's a breakthrough technology; they want AI to generate a good return on investment, whether by solving specific problems, saving money, or increasing sales. If an AI vendor tried to offer a horizontal solution, the value proposition might not be as compelling.[12]
Part of the solution to Brazil's technological backwardness involves building an ecosystem fueled by private institutions, universities, and governments.[3]
1 2 GT-IA da Academia Brasileira de Ciências (2023). Recomendações para o avanço da inteligência artificial no Brasil. Academia Brasileira de Ciências. ISBN978-65-981763-0-3.
Rao, S. V. A., Kondaiah, K., Chandra, G. R., & Kumar, K. K. (2017). A Survey on Machine Learning: Concept, Algorithms and Applications. International Conference on Innovative Research in Computer and Communication Engineering. ISSN 2302-9708
Pedro, E. D. A., Panizzon, M., & Weber, C. G. (2023, November). OHS Professionals AI Adoption: A UTAUT Research in Brazilian Industry. In 2023 15th IEEE International Conference on Industry Applications (INDUSCON) (pp.850–857). IEEE.
Aniceto, D. K. (2025). The Role of Artificial Intelligence (AI) and Machine Learning (MI) in the Oil and Gas Industry. Journal of Technology and Systems, 7(1), 6–27.
Cardoso, L. A. S., Mesquita, B. D. R. de, & Farias, P. R. S. (2025). Use of machine learning algorithms in the context of sugarcane in Brazil: a review. Iran Journal of Computer Science. https://doi.org/10.1007/s42044-025-00250-y.
Leite Coelho da Silva, F., da Costa, K., Canas Rodrigues, P., Salas, R., & López-Gonzales, J. L. (2022). Statistical and Artificial Neural Networks Models for Electricity Consumption Forecasting in the Brazilian Industrial Sector. Energies, 15, 588 . https://doi.org/10.3390/en15020588. DOI: 10.3390/en15020588
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