Brazilian Enterprises Industrialize GenAI Programs

Information Services Group (Nasdaq: III) published a report examining how Brazilian enterprises are moving generative AI into established operations.

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Organizations turn investments toward stronger data foundations, GPU infrastructure and measurable value, ISG Provider Lens^® report says

SÃO PAULO--(BUSINESS WIRE)-- Organizations in Brazil are expanding the use of generative AI across established operations to improve productivity, manage costs and support decision-making, according to a new research report published today by Information Services Group (ISG) (Nasdaq: III), a global AI-centered technology research and advisory firm.

The 2026 ISG Provider Lens^® Generative AI Services report for Brazil finds that the market is moving toward industrialization of GenAI as companies replace isolated initiatives with deployments that provide for continuous development, integration, monitoring and improvement. Models adapted to the Portuguese language and Brazil’s national context are broadening the applicability and accuracy of AI solutions in the country.

“Enterprises in Brazil are setting clearer expectations for GenAI programs,” said Steve Hall, chief AI officer, ISG. “They are linking investments to measurable outcomes while preparing their data, technology and teams for even wider use of both GenAI and agentic AI.”

Enterprises are replacing AI access and deployment metrics with measures linked to business KPIs, and they are less willing to fund proof-of-concept projects without demonstrated returns. As companies integrate GenAI into established workflows instead of replacing core business systems, they are assessing results in terms of cost reduction, execution time, quality, revenue growth and customer experience. As GenAI applications enter production and increase token consumption, companies are implementing cost control through LLM operations (LLMOps) practices that monitor usage, performance and quality while optimizing model selection and setting limits.

The continued expansion of Brazil’s AI market will depend on computing capacity, connectivity and cloud environments. Data quality, availability and accessibility remain common obstacles to realizing value at scale. Companies are modernizing their technology foundations through cloud migration, GPU-enabled infrastructure and centralized data platforms. These can include data lakes, data warehouses and vector databases that support large language models (LLMs) and retrieval-augmented generation.

Adoption of AI agents in Brazil is expected to begin with use cases involving repetitive tasks with measurable results. While highly regulated organizations will deploy specialized agents in controlled environments, midsize companies are likely to turn to managed services. Employee skill gaps, training challenges and resistance by leaders may slow agentic AI adoption, ISG says.

“Brazil’s AI market requires solutions that reflect local language, business needs and operating conditions,” said Adriana Frantz, lead author of the report. “Companies that combine sound data foundations with effective workforce preparation will be better positioned to create value.”

The report also explores other AI-related trends in Brazil, including rising demand for providers to simplify adoption and the increasing use of reusable components.

For more insights into the GenAI-related challenges facing enterprises in Brazil, along with ISG’s advice for overcoming them, see the ISG Provider Lens Focal Points briefing here.

The report evaluates the capabilities of 47 providers across four quadrants: Strategy and Consulting Services — Large Providers, Strategy and Consulting Services — Midsize Providers, Development and Deployment Services — Large Providers and Development and Deployment Services — Midsize Providers.

The report names A3Data, Accenture, AI/R, BRQ, CI&T, Dedalus, Falconi, IBM, Ília, MadeinWeb, NTT DATA, Peers, Stefanini, TIVIT, Valcann and Xertica.ai as Leaders in two quadrants each. It names Deal, Deloitte and T-Systems as Leaders in one quadrant each.

In addition, Capgemini and Skopia are recognized as Rising Stars — companies with a “promising portfolio” and “high future potential” by ISG’s definition — in two quadrants each.

Customized versions of the report are available from A3Data, BRQ, Ília and MadeinWeb.

The 2026 ISG Provider Lens Generative AI Services report for Brazil is available to subscribers or for one-time purchase on this webpage.

About ISG

ISG (Nasdaq: III) is a global AI-centered technology research and advisory firm. A trusted partner to more than 900 clients, including 75 of the world’s top 100 enterprises, ISG is a long-time leader in technology and business services that is now at the forefront of leveraging AI to help organizations achieve operational excellence and faster growth. The firm, founded in 2006, is known for its proprietary market data and research, in-depth knowledge and governance of provider ecosystems, and the expertise of its 1,500 professionals worldwide working together to help clients maximize the value of their technology investments.

View source version on businesswire.com: https://www.businesswire.com/news/home/20261111808629/en/

Press Contacts:

Laura Hupprich, ISG
+1 203-517-3132
laura.hupprich@isg-one.com

Thábata Mondoni, Mondoni Press for ISG
Mobile: +55 11 98671 5652
thabata@mondonipress.com.br

Source: Information Services Group, Inc.

Key Terms

llmops technical

LLMOps is the set of practices and tools used to build, deploy, monitor and maintain large language models in production, similar to how a car needs regular servicing and quality checks to run safely. For investors, it matters because strong LLMOps reduces operational risk, controls costs, ensures regulatory and data privacy compliance, and speeds reliable product rollouts—factors that affect a technology-driven company's profitability, scalability and legal exposure.

vector databases technical

A vector database is a specialized storage system that keeps information as compact numerical patterns so computers can quickly find things that are similar in meaning, style, or context rather than by exact words. For investors, that matters because it powers faster, more accurate searches and AI analysis of large document sets—helping spot trends, risks, or opportunities in news, filings and other unstructured data much like a smart index or trained search engine.

retrieval-augmented generation technical

An AI method that combines a conversational language system with live access to external documents or databases, so the AI first fetches relevant facts and then uses them to form its answer. Think of it as an assistant that checks a file cabinet for source papers before replying, which helps reduce mistakes and reveal evidence. For investors it matters because it can produce more accurate, verifiable summaries of filings, news and research, speeding due diligence while still depending on the quality of the underlying data.

large language models technical

Large language models are advanced AI systems trained on vast amounts of text to understand and generate human-like writing, like a very fast reader and writer that learns patterns in words and sentences. They matter to investors because they can change how companies operate—automating customer service, speeding analysis, cutting costs, creating new products—and they introduce risks around accuracy, security and regulation that can affect a firm’s revenue and reputation.