The energy industry and the tech sector have long existed in parallel universes. One is a marathon runner, the other a sprinter.

The energy sector is known for moving at a glacial pace, through decades-long infrastructure cycles that are measured in megawatts and reliability. 

The tech sector, meanwhile, is famous for moving at a breakneck speed, with a philosophy of disruption and innovation.

Marc Spieler has spent his life learning to speak both languages.

As Senior Managing Director for the Global Energy Industry at NVIDIA, Marc leads the company's strategy across the energy sector, from oil and gas operations to grid intelligence, power utilities and clean energy deployment. 

For the role, he has drawn on his 13 years of experience at Halliburton, one of the energy industry’s largest product suppliers.

“The impact of energy on the world is robust,” Marc says. “It touches nearly everything we do on such a global scale.”

“As we enter the fourth industrial revolution, AI will impact every corner of our lives in the next three to five years.”

His move from traditional energy to Silicon Valley was less of a leap than it might appear. 

“What has shaped my path most is a belief that major industries only transform when technology is paired with deep domain expertise,” he reflects. 

“My time in traditional energy taught me how consequential these systems are and how important trust, safety, and long investment cycles are. 

“At NVIDIA, I saw an opportunity to bring breakthrough computing to a sector that underpins modern life, and to help bridge the gap between what is technically possible and what is operationally practical.”

A five-layer cake

To understand how NVIDIA thinks about energy, Marc reaches for a memorable analogy. 

AI, he explains, is best understood as a five-layer cake: energy, chips, infrastructure, models and applications. Energy sits at the very base. Without it, nothing above it functions.

That framing shapes everything about NVIDIA's approach to the sector. The firm sees itself not as a technology vendor selling tools into an adjacent market, but as a partner whose own business depends on solving the same problems its customers face.

“The relationship has become bidirectional,” Marc explains. 

“The world needs energy to power AI factories, while the energy industry needs AI to modernise infrastructure, intelligently distribute energy resources and accelerate decarbonisation. 

“That mutual dependence is driving some of the most consequential collaborations the sector has seen.”

It is a relationship he is keen to distinguish from the many technology waves that have washed over the energy industry before – most of which have receded without transforming it. 

“We need to be credible to an energy industry that has seen many technology waves come and go,” he acknowledges, “while making the case that this one is fundamentally different.”

The pace problem

But while AI has so much transformational potential, keeping up with the speed at which it evolves can be difficult.

“The pace mismatch is the biggest challenge,” he says. “AI is moving at a speed the energy industry is not used to, and the industry operates on timescales AI companies are only beginning to appreciate.”

That tension is visible in the numbers. “Infrastructure built today will still be operating in 2050,” Marc explains.

As such, decisions made in boardrooms this year are being measured against ROI timelines that sometimes stretch across multiple generations of technology, meaning that novelty is not much of a selling point.

“The energy sector makes decisions measured in decades,” he says. “That time horizon demands a different kind of conversation – one grounded in deep industry knowledge, long-term relationships and proof points that speak the language of reliability and return on investment, rather than novelty.”

Reliability, in particular, is non-negotiable. Far from being an obstacle to AI adoption, Marc argues that the industry's zero-failure mindset should function as a design requirement.

The tool he returns to most often is the digital twin. Siemens Energy, for instance, is using NVIDIA's Omniverse platform and PhysicsNeMo to build digital twins of complex grid components, simulating thousands of failure scenarios before any change touches live infrastructure. 

“That is exactly the kind of deployment that the energy industry can trust,” Marc says, “because it earns its place through rigorous validation before it ever touches anything real.”

The scale of the demand challenge

Beyond reliability, the most pressing challenge Marc identifies is one that sits at the intersection of both industries: the sheer scale of electricity demand that AI infrastructure is creating.

“The buildout of AI infrastructure alone represents the largest infrastructure investment in history,” he says, “layered on top of already accelerating electricity needs from transportation electrification, heating and population growth.” 

In many regions, grid interconnection queues now stretch for years, and new generation capacity is not coming online fast enough to keep pace.

NVIDIA's response operates on two fronts. The first is efficiency. Since 2016, the company has improved energy efficiency for AI training by 3,000 times and for inference by 45,000 times. 

The firm’s forthcoming Vera Rubin architecture is expected to deliver up to 100 times more performance per watt than its current Blackwell generation, while a full transition to liquid cooling will reduce water consumption by a factor of 300 compared to traditional air-cooled systems. What’s more, it will have the added benefit that the water used can be 45°C, eliminating the need for chillers entirely.

The second front is infrastructure design. Together with Emerald AI and a group of major generators including AES, Constellation, Invenergy, NextEra Energy and Vistra, NVIDIA is developing a new class of AI facilities designed to be flexible in how they consume and store energy.

Research from Duke University suggests that if data centres flex their demand for just a few hours each year, the US could absorb around 100 GW of new load without expanding generation capacity.

“The opportunity for the technology industry,” Marc says, “is to treat energy as a co-design challenge, not a cost to be procured.”

Accelerating the clean energy transition

Some of the most compelling applications Marc describes are on the clean energy side. Geothermal development, long constrained by the difficulty and expense of identifying viable well sites, is being transformed by AI-enhanced seismic imaging.

Nuclear energy, which is undergoing a huge revival in public and commercial interest this year, is seeing digital twins used to enable autonomous reactor operations and compress permitting timelines that have historically taken years. 

At CERAWeek earlier this year, Microsoft and NVIDIA announced a collaboration providing end-to-end tools to streamline nuclear permitting, accelerate plant design and optimise operations across the industry.

On solar, NVIDIA partner Maximo recently completed a 100MW robotic installation at AES' Bellefield site using AI-driven robotics built on NVIDIA's accelerated computing platform.

The road ahead

Ask Marc where he expects the energy and technology industries to stand in five years, and the answer is unequivocal. “The lines between the two industries will be considerably harder to draw,” he notes. 

AI infrastructure will be integrated into grid operations, participating in demand response and frequency regulation, co-located with generation assets in configurations that today exist only as pilots.

The choices being made now, he argues, will determine the shape of that convergence – how fast, how broadly and how responsibly it unfolds. 

“The processes that today take years – permitting, interconnection studies, construction – can be compressed through AI-powered digital twins, automated engineering workflows and intelligent grid integration tools.”

For an industry accustomed to measured timescales and proven technology, that represents a genuine inflection point. Marc’s task is to make sure the energy sector is ready for it, and that NVIDIA is the partner standing alongside it when the time comes.