Nvidia Sees Mexico in the Early Stages of AI Adoption
Marcio Aguiar, the Director of Enterprise for Nvidia in Latin America, highlighted that Mexico is entering an early phase of artificial intelligence (AI) adoption. He described the country as “awakening” and taking steps to close gaps with global leaders, such as the United States and China.
Mexico and Brazil: Not Ahead or Behind, but Awakening
Aguiar clarified that neither Mexico nor Brazil are ahead or behind in AI; instead, they are both “awakening” and working towards developing their own infrastructure and capabilities without relying on external technologies.
He emphasized that the recent surge in AI generative models has contributed to changing public perception of Nvidia, but the technological shift began earlier.
“Since 2010, we have focused on penetrating the corporate market through software techniques and applications, as well as new hardware architectures,” Aguiar explained.
The turning point for Nvidia’s visibility came in 2022 when OpenAI revealed that it trained its model using Nvidia’s graphics processing units (GPUs). Since then, the brand has been recognized as a central piece of the new computing era and the AI wave that has swept across the world.
However, Aguiar clarified that this was not a radical shift but an organic process supported by years of collaboration with researchers and startups.
From Chip Manufacturer to AI Infrastructure Provider
Nvidia has transitioned from being a chip manufacturer to becoming an AI infrastructure provider, according to Aguiar. The company now delivers the entire infrastructure and necessary components for businesses to set up their own data centers.
Nvidia works with all major data centers worldwide but does not operate its own centers; instead, it enables partners to build and manage them. The company’s proposal combines hardware and software for corporations to develop products based on this foundation, in a market with exponential growth.
No AI Bubble: Understanding the Current Technological Landscape
Aguiar dismissed the notion of an “AI bubble” and attributed it partly to a misunderstanding of the current technological phase. He distinguished between AI as a decades-long field and the recent phenomenon of AI generative models, which “transform any data into new data” and have multiplied use cases across various industries.
He illustrated his point with a nearby example: Formula 1, which relies on fluid dynamics simulation and stability supported by accelerated computing and AI to design safer cars annually.
Aguiar acknowledged a disparity between demand and available talent.
“There is a much greater demand than there are people trained,” he said.
For this reason, Nvidia collaborates extensively with universities to train the next generation of engineers and scientists.
Getting Started with AI in Mexico
Aguiar offers a practical guide for starting with AI in Mexico: “Think big, but start small.” The key is to identify critical business processes and prioritize their automation using AI techniques rather than attempting large-scale projects that may stall due to fear or uncertainty.
He also warned against blindly copying competitors. Each organization should map its unique needs and adoption sequence.
Mexico’s immediate challenge is to turn this “awakening” into concrete and sustainable steps: investment, training, and projects with clear objectives.
On both public and private fronts, the window is open to align talent with infrastructure and use cases that boost productivity and competitiveness.
Aguiar’s recommendation is to align executive bodies and technical teams to decide which processes to automate first, how to measure results, and how to scale without losing focus.
“If governed with short iterations and rapid learning, results will emerge,” he asserted.
Nvidia bets that the next stage of AI adoption in the region will be defined by companies that internalize their own or partner-provided infrastructure and develop business solutions on accelerated computing platforms.
Mexico, which has demonstrated a growing appetite for investment and training, has the opportunity to narrow the gap if it turns that appetite into well-governed projects and available talent.
The picture is one of a country not arriving late but starting its journey. An emerging yet results-oriented agenda with opportunities in critical process automation and an urgent task of human capital formation.
