AI is a powerful tool for transforming organizational processes across all areas, including human resources, legal, supply chain, R&D, and marketing. An IDC survey shows that more than a third of technology leaders believe that AI is already disrupting their business, and 88% expect it to have at least a moderate impact on their business by the end of 2025.

 

The aforementioned study also highlights that CIOs will play a strategic role in developing comprehensive roadmaps, governance structures, and AI economic models that align IT investments with business objectives to drive responsible growth.

 

When should we begin the journey towards AI?

 

It is not enough to adopt AI because it is a trend; industries must identify where AI can generate a measurable impact within the business.            Therefore, the questions would be: Can we optimize our logistics routes? Improve cybersecurity? Increase commercial efficiency?

 

To achieve successful AI adoption, it's important that your mission-critical IT infrastructure is ready so that AI deployments don't slow down or overload workloads. Regarding implementation, companies can choose from the following options:

 

·       Modernization (Retrofit): Modernize legacy data centers with GPU-accelerated platforms and AI-optimized applications, while leveraging advanced and scalable critical digital infrastructure in power and cooling for mixed applications.

 

·       New Build: Start with designs created specifically for the intense power and cooling demands of AI, enabling greater efficiency, supporting high-density workloads, and future-proofing the infrastructure.

 

Alternative energy options such as fuel cells and next-generation batteries can improve resilience and optimize carbon emissions, while liquid cooling can provide efficient heat removal for these dense applications.

 

“ Regardless of the path you choose—modernization or new build—the key is to align your IT infrastructure with the performance demands of AI through scalable and flexible solutions. Intentional design and modernization allow your systems to support accelerated computing at scale, avoiding bottlenecks and minimizing wasted investments ,” says Alex Sasaki, Vice President of Sales for Vertiv Latin America.

 

 

 

 

 

Impact of high density on critical infrastructure

 

GenAI's processing demands rely on high-performance GPUs and CPUs, which is increasing the density of computing environments and placing new pressure on the critical digital infrastructure that supports these intense workloads.

 

NVIDIA LATAM's Regional Sales Manager, Guilherme Fuhrken, explained that while GPU-accelerated platforms reduce the number of physical servers required for a task, AI workloads still consume significantly more computing power than traditional applications. As a result, data centers must adapt to support much higher power densities. GPU-based systems offer key advantages: they reduce operating costs, decrease space usage, accelerate deployment, and improve energy efficiency. Transitioning from CPU-only systems to GPU-accelerated systems can save more than 40 terawatt-hours of energy per year, based on workload output—equivalent to the electricity consumption of nearly 5 million homes in the United States.

 

However, this efficiency also presents challenges: AI operations demand significantly more computing power than previous workloads, pushing energy density to new extremes. Industry projections show densities reaching 1 MW by the end of the decade. Regarding this, Sasaki states, " Keeping pace with this change requires significant improvements in power delivery, cooling systems, and facility design. High-density power and cooling solutions are now specifically designed to support the next generation of GPUs, enabling compute-intensive AI workloads to run securely, with maximum performance and high availability."

 

Collaboration to respond to AI

 

With this new landscape presented by AI, where data centers with 100,000 GPUs are already being observed, it is necessary to provide reliable, high-density power supply systems, as well as efficient heat dissipation, to support the next generation of computing. This requires collaboration among chip manufacturers, infrastructure designers, utility companies, and data center operators to create an ecosystem capable of integrating critical infrastructure and IT.

 

Recognizing the benefits of closer partnerships in the industry, Vertiv integrated its power and cooling solutions with NVIDIA's modern platforms to help customers meet the needs of compute-intensive applications and support the development and deployment of AI infrastructure worldwide.

 

It's important to know that while traditional data centers weren't designed for loads exceeding 100 kW per rack, that doesn't mean they have to become obsolete. With upgrade strategies focused on power infrastructure, they can be adapted to support high-density deployments and mixed workloads, including those required by advanced AI and other compute-intensive applications.

 

“ Today, technology developers can help companies and sectors throughout Latin America rethink their mission-critical IT infrastructure in the age of AI, with innovative portfolios and essential advice that responds to the challenges and opportunities of digital evolution,” Sasaki concluded.