Unleashing energy technology to create a sustainable, resilient future

Artificial intelligence (AI) is redefining global energy infrastructure.

The world’s largest AI data centres (also known as AI factories) currently consume as much power as some cities. And global data centre electricity demand is expected to double to 945 TWh by 2030, according to the International Energy Agency – matching that of many industrial nations.

But this explosive demand is coinciding with fresh volatility across energy and geopolitics. Against such a backdrop, the world cannot rely on 20^th century infrastructure.

This is the fundamental paradox of the modern economy. AI is the digital engine of growth, but it is also a massive consumer of one of the world’s most in-demand resources – energy. And here's the twist: AI is also the very technology we need to optimize the energy, infrastructure and systems it is powering.

The choice is no longer "green versus dirty", it’s now a choice between growth and stagnation.

As AI demands more energy, only smarter, more resilient technology can deliver it. Unlocking the next wave of growth and innovation will depend on two essentials: efficiency, which means using less energy to do more, and resilience, which means building energy systems that can anticipate, absorb and adapt to disruption and change.

The old energy model was simple. A rigid, one-way, linear flow from large central generation plants to passive, unquestioning consumers. That world is gone. The new energy landscape is decentralized, omni-directional, software-defined and data-driven. Homes, buildings and factories are evolving from passive endpoints into active, intelligent participants.

This transformation is powered by the convergence of electrification, automation and digitalization – this is what defines modern energy technology. In a volatile, multipolar world, a digitalized grid is a resilient grid. It bends, rather than breaks. Digital tools make waste visible and removable, creating greater efficiency – the fuel you do not have to buy. And while efficiency is the mechanism for growth, resilience is the insurance policy against instability.

Today’s AI factories do not manufacture goods, they produce intelligence measured in tokens, which are the units of data that power AI models. The more tokens generated, the more power, cooling and optimization needed. That reality is pushing power densities to levels that require a fundamental redesign of both physical and digital energy infrastructure.

This is a data and intelligence challenge as much as a hardware one. Advancing energy technology means integrating the Internet of Things, digital platforms and AI to optimize everything from grids and data centres to buildings and industry.

Meeting this challenge will require energy systems that are not only electrified and automated, but deeply integrated with digital intelligence. Today, vast amounts of data flow through devices, platforms and industrial processes, but much of it remains fragmented and hard to act on. Without context, optimization stalls. With context, AI can forecast demand, simulate scenarios and recommend actions that improve reliability, cut waste and scale efficiency.

To achieve this, energy systems need a foundation that brings structure and meaning to data. That means seamless integration of data from device to edge to cloud, digital twins that evolve across the entire asset lifecycle and multi-domain expertise that includes real-world knowledge of energy and automation systems.

Bringing these dimensions together will enable energy and industrial intelligence. This means advanced models that can interpret entire systems, adapt to changing conditions and drive efficiency at scale. By combining physics-based reasoning with operational context, this intelligence can continuously learn and improve across the lifecycle. Looking ahead, emerging capabilities such as agentic workflows will extend this progress, moving from insight to autonomous action – but always with human oversight.

To realize these benefits, energy and industrial firms need AI that is deeply embedded in both the physical and digital worlds. This energy technology is already enabling unprecedented capabilities today and it will enable even more in the future, including:

Technical innovation, data-driven intelligence and ecosystem thinking can help solve the paradox of digital growth versus energy constraint. Ultimately, the smartest algorithm cannot fix inefficient infrastructure. Measurement is the foundation, only then is optimization possible.

While technology can provide the tools, ecosystems deliver the scale needed to transform energy systems. But the energy paradox is too vast and complex for any single company or government to solve alone – fragmented, siloed innovation is guaranteed to fail.

Building open ecosystems where technology, business partners and people can co-create requires radical public-private cooperation. A commitment to open standards, shared data frameworks and cross-industry partnerships is crucial.

The entire value chain must engage in this process – from electricians and system integrators to entrepreneurs and policy-makers. This is how innovation achieves true, measurable impact that enables efficiency and resilience to scale from sites to sectors to societies.

AI has become both the digital engine for growth and a massive consumer of the world’s most in-demand resources. The resulting defining moment requires an immediate, collective response – incremental change and siloed action are not enough.

There is no AI at scale without energy intelligence.

The future belongs to those advancing energy technology and making efficiency and resilience the standard for every breakthrough. This is the only way to turn complexity into our greatest global opportunity.