Alberto Chiesara Sanchez on Building the Infrastructure for AI with Uninterruptible Power

We supply the energy that fuels the generators. And when the project is ready for permanent infrastructure, we pack up and move to the next one.

May 26, 2025
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The artificial intelligence boom has brought an explosion in demand for electricity-hungry data centers. A single hyperscale data center now consumes as much electricity as 80,000 households. According to the International Energy Agency, global data center power consumption is expected to quadruple by 2030, driven by AI model training, inference, and nonstop cloud computing. That’s not just a capacity issue, but an issue of resilience. AI workloads demand uninterruptible power, low latency, and the ability to scale at a pace the traditional grid can’t match.

At the center of this emerging energy crisis is Alberto Chiesara Sanchez, President of Hydria Gas Technologies, a company solving the ‘time-to-power’ problem that’s paralyzing AI infrastructure deployment. “Everyone is focused on the power of AI,” Chiesara says. “But very few are thinking about the power behind AI, the actual energy that keeps it alive, especially when the grid can’t.”

Hydria

Today, when an AI or data center developer secures land, preparing themselves to build their dream, the first call is to the local utility. But that conversation is often a dead end. The delay drives organizations to seek alternatives like Hydria for an efficient, flexible solution. Using a network of trailers, fixed on-site storage, and compression stations, Hydria creates virtual pipelines that deliver compressed natural gas (CNG), even hydrogen, directly to the site, allowing facilities to get online in months, not years.

“We don’t supply power directly,” Chiesara clarifies. “We supply the energy that fuels the generators. And when the project is ready for permanent infrastructure, we pack up and move to the next one.”

Alberto Chiesara, President of Hydria

Alberto Chiesara Sanchez, President of Hydria Gas Technologies

In today’s volatile energy landscape, organizations have been shown two choices. The first one is uninterruptible natural gas contracts at two to four times the cost of standard rates. The other choice is relying on interruptible gas, knowing it could be cut at any moment.

Hydria offers a third way. By combining cost-effective, on-site storage and compression systems, Hydria lets companies ‘time shift’ their energy use, obtaining gas when it’s inexpensive (like weekends or overnight) and storing it for high-demand periods. “We’re a virtual pipeline and battery, all at the same time,” says Chiesara. “We let clients optimize cost without sacrificing reliability.”

It’s a solution that’s not only smarter but also scalable. Hydria’s systems are modular and mobile, meaning energy can be delivered just in time, like freight, without being tethered to permanent infrastructure. This allows AI companies to scale at the speed of innovation without being held hostage by long utility timelines or unsustainable energy costs.

Regulators love it. Unlike diesel generators, which are polluting, loud, and heavily regulated, Hydria’s natural gas and hydrogen systems are cleaner and quieter, with lower emissions and greater operational efficiency.

What makes Chiesara especially effective is his blend of technical expertise, financial acumen, and global insight. Having worked across three continents within major institutions, he brings a unique perspective to the energy space grounded in practicality, innovation, and inclusion.

That is why Chiesara’s vision for AI-powered infrastructure is rooted in both immediate pragmatism and long-term sustainability. For instance, the cleaner alternative to diesel, Hydria’s mobile CNG units provide flexible backup energy for areas with unreliable grids or no pipelines. On the other hand, as hydrogen fuel cells gain traction, Hydria is developing systems to deliver long-duration, zero-emission energy. It is truly ideal for AI operations looking to future-proof against emissions regulations and grid instability.

“AI can’t wait for the grid to catch up,” Chiesara confirms. “We have to build the necessary infrastructure that is just as smart, distributed, and resilient as the algorithms they support.”

For all its complexity, the Hydria model is simple at its core: energy that moves like data and power that’s as dynamic, scalable, and resilient as the AI systems it supports. It’s not just for Big Tech. Hydria’s mobility means rural areas, developing regions, and underserved communities can access high-performance energy, too, fueling not only data centers but hospitals, logistics hubs, and schools. “If we build it right, with flexibility and foresight, we unlock innovation everywhere,” Chiesara concludes.

The artificial intelligence boom has brought an explosion in demand for electricity-hungry data centers. A single hyperscale data center now consumes as much electricity as 80,000 households. According to the International Energy Agency, global data center power consumption is expected to quadruple by 2030, driven by AI model training, inference, and nonstop cloud computing. That’s not just a capacity issue, but an issue of resilience. AI workloads demand uninterruptible power, low latency, and the ability to scale at a pace the traditional grid can’t match.

At the center of this emerging energy crisis is Alberto Chiesara Sanchez, President of Hydria Gas Technologies, a company solving the ‘time-to-power’ problem that’s paralyzing AI infrastructure deployment. “Everyone is focused on the power of AI,” Chiesara says. “But very few are thinking about the power behind AI, the actual energy that keeps it alive, especially when the grid can’t.”

Hydria

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