Brazil's 100 MW Data Center Contributes BRL 1.5 Billion to GDP and BRL 590 Million in Labor Income
2026-07-08 09:47
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en.Wedoany.com Reported - A study by the FGV (Getulio Vargas Foundation) shows that a 100-megawatt (MW) data center can directly and indirectly generate a total of BRL 1.5 billion in Gross Domestic Product (GDP) growth and BRL 590 million in labor income for Brazil, with these benefits distributed across multiple economic sectors such as construction, commerce, and engineering services.

Data Center Funding

The study, titled "Potential Socioeconomic Impacts of Brazil's Consolidation as an International Digital Infrastructure Hub in the Era of Artificial Intelligence," was compiled by FGV and released on Tuesday (July 7). It found that constructing a data center requires a total investment of BRL 25 billion, with BRL 5 billion allocated to infrastructure and BRL 20 billion to computing equipment (including servers, GPUs, and storage). This process is expected to create approximately 12,560 direct and indirect jobs across the production chain, with a construction period of 18 to 36 months.

Once operational, the data center will permanently sustain about 15% of the construction-phase jobs. The study details were jointly released in Brasília by the Free Market Institute (Instituto Livre Mercado, ILM), the Brazilian Association of Infrastructure and Basic Industries (Associação Brasileira da Infraestrutura e Indústrias de Base, Abdib), the Brazilian Association of Software Companies (Associação Brasileira das Empresas de Software, ABES), Brasscom, Dig.IA, and the Brazilian Competitiveness Movement (Movimento Brasil Competitivo, MBC). In the data center sector, for every BRL 1 million invested, approximately BRL 350,000 in labor income is generated, of which BRL 259,000 is in direct wages and BRL 91,000 comes from compensation in supplier industries. Wage benefits cover IT professionals and extend to workers in sectors such as construction, transportation, commerce, and food.

The study points out that consolidating Brazil's position as a digital hub depends on the integration of hardware, software, connectivity, and energy, which are the foundations of digital infrastructure. At the same time, the demand for computing power driven by artificial intelligence is growing, and strengthening the production chain and technology ecosystem, including suppliers, innovation, and workforce training, is also a necessary condition.

Commissioned by Scala Data Centers and Norgás, the survey concludes that Brazil's predominantly renewable energy matrix, available land, domestic market size, and geographic location give it an advantage in competing for data center and AI infrastructure projects. One scenario envisioned by FGV shows that the country's digital infrastructure installed capacity could grow from approximately 1 gigawatt (GW) to 13.7 GW by 2035. This expansion could support over 230,000 permanent jobs. To achieve the additional 12.7 GW of capacity, investments of between USD 431.8 billion and USD 698.5 billion, equivalent to approximately BRL 2.3 trillion to BRL 3.7 trillion, would be required, covering the physical infrastructure of the projects and computing equipment for data processing and AI applications.

The power sector faces challenges. Although the renewable energy matrix is seen as a competitive advantage, FGV notes that the country needs to better coordinate grid expansion with the growth in data center demand and improve the predictability of system access for large projects. Regulatory fragmentation and instability in tax incentives are also cited as sources of uncertainty for investors. To address these obstacles, the study proposes policies to stimulate domestic equipment production, a stable legal framework for tax incentives, and recommendations for recognizing data centers as strategic infrastructure for the power sector. FGV also suggests establishing a national-level coordination body to connect the government, regulators, and the private sector, aiming to reduce overlapping functions and enhance project predictability.

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