If competitiveness today is driven by innovation, how can you be sure your IT infrastructure is ready to sustain the exponential growth of emerging technologies? In the current economic landscape, where data is seen as the primary catalyst for digital evolution, organizations across all industries are engaged in a strategic race to build more scalable and resilient Data Centers, optimizing their infrastructure for artificial intelligence.

As applications like machine learning and generative AI redefine entire value chains, the ability to handle massive volumes of data and process them efficiently is no longer a competitive advantage—it has become a matter of market survival.

Now more than ever, Data Centers are at the core of digital acceleration strategies, operating as mission-critical infrastructure. To meet future demands, IT leaders and infrastructure providers must rethink technology environments, investing in accelerated servers, high-performance storage, and sustainable architectures.

This race for innovation is reshaping the industry, distinguishing leaders from followers.

In this article, we will explore how AI-ready infrastructure is evolving to meet these demands. We’ll examine global and regional trends, highlighting Brazil’s role as one of South America’s key emerging hubs. More than just keeping up now is the time for companies and technology executives to lead this transformation. Read on to learn how.

Global growth of AI infrastructure: figures and projections through 2028

The modernization of artificial intelligence infrastructure is accelerating rapidly, solidifying itself as one of the core pillars of the digital economy. According to research conducted by IDC, the global AI infrastructure market reached $31.8 billion in the first half of 2024, marking an impressive 37% increase compared to the same period in the previous year.

Projections indicate that this segment will surpass $100 billion by 2028, driven by the widespread adoption of machine learning models, generative AI, and automation systems on a global scale.

A substantial portion of this growth is anchored in the advancement of accelerator-integrated servers, which now account for 58% of AI server investments and are essential to meeting intensive processing demands. Additionally, 65% of these investments are being allocated to cloud environments, where hyperscale providers and digital service companies lead the development of scalable and highly connected infrastructures.

However, many traditional enterprises still face challenges in modernizing their on-premises infrastructures, often constrained by budget limitations or a lack of technical expertise.

Regional market trends

The United States continues to lead as the largest AI infrastructure market, accounting for nearly half of global investments in 2024. However, other regions are rapidly expanding their footprint. The Asia-Pacific region, for instance, is expected to see the highest compound annual growth rate (CAGR) of 20% through 2028, while Brazil and other South American countries are emerging as key strategic AI hubs.

This sustained development reflects the growing confidence of both governments and private enterprises in AI as a driving force for digital transformation.

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South America as a global AI growth hub

Brazil is emerging as one of the world’s leading hubs for artificial intelligence infrastructure, solidifying its position as the technological epicenter of South America. Recent data shows that the country is expected to absorb 75% of regional Data Center investments in the coming years, reinforcing its leadership in installed capacity and expansion. This rapid growth is driven by a combination of strategic factors: the availability of renewable energy, rapidly developing infrastructure, and a geographically advantageous location.

Additionally, the South American Data Center market is projected to expand by 68% by the end of the decade, with Brazil playing a central role in this evolution. Forecasts indicate that regional energy consumption will reach 1,810 MW by 2029, growing at an average annual rate (CAGR) of 9.37%. Brazil is also experiencing robust revenue growth, with market size expected to increase from $2.07 billion in 2024 to $3.5 billion in 2029, reflecting the rising demand for AI-driven solutions in industries such as healthcare, finance, and agribusiness.

By attracting the largest share of investments and hosting strategically positioned cities—such as Campinas, Fortaleza, and Brasília—Brazil is solidifying itself as one of the most promising AI and Data Center markets globally.

How infrastructure for artificial intelligence is transforming Data Centers

Artificial intelligence is redefining the architectural standards of modern Data Centers. The surging demand for computational power has led to the creation of massive clusters, expanding processing capacity to levels that would have been unimaginable just a few years ago. These advancements are driven by the need to train and deploy increasingly complex AI models, requiring specialized servers and ultra-high-performance storage.

This evolution is not just about scalability—it is a core strategy to support innovation and meet the demands of new digital consumption patterns.

Enhancing AI-ready infrastructure calls for innovations that extend beyond energy efficiency and geographic location. Some emerging strategies include the adoption of smaller, more focused AI models, which consume fewer computational resources without compromising performance. When combined with distributed cluster architectures, these approaches provide a critical balance between scalability and efficiency.

Another key trend is the development of more efficient AI technologies. Smaller, more specialized AI models are gaining traction, reducing the need for large-scale processing clusters while maintaining effectiveness.

Sustainability in infrastructure for artificial intelligence: challenges and solutions

As infrastructure requirements become more demanding, there is growing pressure for energy efficiency and sustainability. AI models—particularly those involving large-scale machine learning—can consume up to ten times more energy than traditional systems. With the global demand for computing power and storage rising yearly, finding sustainable solutions has become a strategic priority.

With Data Centers consuming increasingly high volumes of electricity, many organizations are relocating their operations to colder climates and regions with access to renewable energy sources. This approach reduces operational costs and aligns with global sustainability initiatives. The result is a new generation of Data Centers designed to be efficient, resilient, and environmentally responsible.

Additionally, there is a growing push to implement more efficient cooling systems—such as Delta³—and to design architectures that minimize energy waste.

At the same time, innovations in nuclear energy for Data Centers and the adoption of long-duration battery solutions are being explored as viable alternatives to ensure energy stability. Embracing these advancements will be essential for companies to balance technological growth with environmental responsibility.

Strategies for the coming months

Infrastructure for artificial intelligence is at the core of the global technological revolution, shaping markets, supply chains, and corporate strategies. From the expansion of the global market to the strategic role of Brazil and South America, the data is clear: AI-driven digital evolution demands bold and innovative investments in Data Centers. For technology leaders, now is the time to align operational decisions with industry trends and anticipate future demands.

Beyond capacity expansion, sustainability has become an unavoidable challenge. The adoption of renewable energy sources, efficient cooling systems, and more compact AI models are just some of the emerging solutions to balance growth with environmental responsibility. Competitiveness in the global market will depend on the ability to implement resilient infrastructures that adhere to best practices in energy efficiency.

The future of artificial intelligence is full of opportunities—but also risks for those who fail to act with strategic foresight. Now is the time to invest in intelligent hubs, explore sustainable solutions, and lead the transformation.

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