Fuelling change: how to drive fundamental change in the energy system

The Energy Transition is among the most significant changes the world has ever seen. In the coming decades, it will remake the global energy system for a low- or no-carbon future, and in the process impact the lives of virtually every person on the planet in one way or another. While change on such a scale is challenging, it also represents a historic opportunity.

As the energy system continues to evolve, asset-intensive industries are investing in a wide range of technologies – from renewable energy, carbon capture and storage, green hydrogen production and more – to help reach their sustainability goals. Underpinning many of those technologies, however, is another – industrial AI.

As the once-solid boundaries between many industries continue to blur, industrial AI is fast becoming a key enabling technology that can deliver the agility, guidance and automation that will help companies navigate the changes to come. Importantly, industrial AIs are built with specific guardrails to ensure they operate in predictable ways.

Enabling new opportunities with AI

Part of the converging of multiple industries can be seen in the decision by many companies to invest in near-term technologies – like carbon capture, biofuels and the hydrogen economy – as a way to reap some sustainability benefits now while also developing long-term solutions for a low- or no-carbon economy.

In recent years, for example, oil and gas companies around the world have made significant investments in carbon capture technology and in solar and wind power. Both have a way to reduce their own emissions, electrify their current operations, and gain a foothold in a market estimated to be more than US$2 trillion by the end of the decade.

AI-enabled digital grid management tools play a key role in supporting those investments by simplifying the process of integrating renewable resources into the grid, allowing operators to better predict generation and optimise the flow of electricity across the grid.

For companies investing in CCUS and hydrogen, industrial AI-driven hybrid modelling tools can offer key benefits. As they can be optimised in real-time, hybrid models can quickly be optimised for the unique conditions at different locations, allowing far faster development and deployment of new technologies.

To optimise those systems even further, generative AI tools can propose improved solvents for carbon capture or new electrolyser designs to increase efficiency. When combined with industrial AI, those tools can be used to maximise carbon capture or green hydrogen production, or in the development of efficient batteries for electricity storage.

The importance of AI guardrails

While it has the potential to deliver massive benefits to companies across asset-intensive industries, it’s also critical that industrial AI has specific guardrails to ensure it remains predictable and understandable.

The risk is that an ‘unleashed AI’ could produce confusing or incorrect results which could cause extremely costly problems, both in terms of damage systems and assets, lost performance and impact on employees and the surrounding community.

Among the key protections built into industrial AI is the understanding that, while AI tools may monitor conditions and make suggestions about what actions to take in certain situations, it is human operators who are ultimately in control of the system.

While industrial AI may one day be able to automate certain decisions, that process depends on building trust among operators that industrial AIs – unlike other, general AIs – are explainable, and not simply a ‘black box.’ In addition, industrial AI systems must be built with expert guidance, ensuring operators understand their possible behaviours.

Ultimately, the world will find ways to overcome the challenges of the Energy Transition, and companies – as they always have – will adapt to the new landscape they find themselves in. Those adaptations may not always be easy to make – fundamentally changing industries that directly touch billions of people’s lives never is, but we have tools today that can help make that process easier.

While some of those changes are already occurring, more are on the horizon, and industrial AI – if deployed carefully and correctly – will be key to delivering a sustainable future that benefits everyone.