Two surveys released this week paint the same picture of the Brazilian AI market: broad adoption, low maturity. A study by Strand Partners for AWS shows half of Brazilian companies already use artificial intelligence in some form, but only 15% have reached an advanced stage of use. A separate survey by ManageEngine, covering 1,000 IT decision makers in Latin America, including 250 in Brazil, reinforces the picture: the conversation inside companies has moved past whether to adopt AI, and is now about turning isolated pilots into real business capability.
The bottleneck shows up in the budget. According to ManageEngine, 76% of organizations in the region put more technology resources into maintenance than into innovation, and only 9% prioritize innovation spending. That helps explain why so many companies say they use AI but so few report measurable gains: whatever budget is left after keeping existing systems running is rarely enough to scale an AI project past the pilot stage.
The same survey points to the three biggest barriers to turning AI investment into return: security and compliance, lack of data and AI talent, and lack of clarity about real use cases. None of these three is a problem of model access or available technology, they are internal organizational problems, the kind of barrier that does not get solved by buying another software license.
One figure stands out for its contrast: Brazil leads the region in self reported maturity, with 32% of companies saying they already moved to a platform centric IT model and 25% describing themselves as "AI orchestrated," the highest shares among the countries surveyed. At the same time, more than half of respondents use between 11 and 25 different technology tools, and 81% say that tool overload has increased operational complexity over the past two years. Brazil appears to be ahead of its neighbors and, at the same time, drowning in its own technology fragmentation.
For a small or midsize company, the practical takeaway from these two surveys is direct: the bottleneck is rarely the lack of a more advanced AI model, it is structural budget spent putting out fires instead of building capability, and the absence of a clear, measurable use case before a project starts. Before signing up for one more AI tool, it is worth answering three simple questions: which technology tools already active in the company are actually being used, how much of the IT budget is locked into maintenance that could be simplified, and which business metric, not usage metric, will prove the AI project was worth the investment.
Sources
TI Inside, Brazil enters a new phase of artificial intelligence, from adoption to scale: https://tiinside.com.br/23/09/2026/brasil-entra-em-uma-nova-fase-da-inteligencia-artificial-da-adocao-a-escala/
Intelligent CIO LATAM, independent coverage: https://www.intelligentcio.com/latam/2026/09/18/76-of-latin-american-organisations-spend-more-on-it-maintenance-than-innovation/
DataCenterDynamics, independent coverage: https://www.datacenterdynamics.com/br/noticias/brasil-lidera-em-ti-centrada-em-plataformas-mas-a-complexidade-operacional-ainda-limita-a-ia-e-a-inovacao/