MIND THE AI GAP
The findings of our survey suggest that the UK has some catching up to do when it comes to investing in AI. Just 40% of UK energy suppliers and investors said they were currently using or investing in AI applications.
Although we need to be careful about drawing too many cross-border conclusions based on varying sample sizes, only APAC and Western Europe showed lower levels of AI use compared to the UK.
However, 46% of UK suppliers and investors reported that they were considering using or investing in AI – one of the largest proportions globally.
Digging deeper, it seems that where AI is being used in UK energy organisations it is most prevalent in more functional activities, such as data mining, maintenance and operational controls as the chart below demonstrates.
More advanced AI areas, such as smart buildings and digital twinning, which have been more readily adopted in the Middle East, have yet to be taken up in a meaningful way in the UK – only 25% of suppliers and investors expect smart buildings to have a serious impact on energy business functions. This slow uptake of advanced AI technologies could hinder the UK’s energy transition by limiting the efficiency and innovation needed to make it a reality.
Despite these findings, which mirror mixed AI adoption levels across many sectors in the UK, the nation still harbours ambitions to become an AI global superpower. However, overcoming barriers is crucial to accelerate AI adoption and, in turn, unlock significant rewards when it comes to energy transition. Cybersecurity is the number one barrier referenced by the energy sector, according to 57% of suppliers and investors, followed by concerns with data storage (40%) as well as privacy and data ownership (40%).
The lag in AI adoption is reflected among commercial consumers too, further highlighting the need to accelerate efforts in order for the UK to take the lead the global energy transition journey. In fact, just 21% of commercial consumers say they are using AI and digitalisation to ensure access to an affordable, reliable energy supply, compared to 44% in Middle East and 41% in APAC.
“Benefits include areas such as predicting consumption based on historic and real-time data, AI demand response management to help balance supply, as well as predictive foresight in maintenance to reduce breakdowns and manage costs. In addition, for renewable energy, AI can help predict the unpredictable such as the weather and the availability of the wind and sun.
"The technology should assist with anticipating these factors as well as the more effective integration of renewable energy into the grid. Yet, its use requires planning and governance, particularly when it comes to training the AI and compliance with any sector regulations. What’s more, the impact of things going wrong for, say, a major energy supplier range from reputational damage to serious and, possibly, catastrophic consequences.
“With that in mind, many were surprised not to see an AI Act feature in the government’s plans when Labour came to power. This could have provided an insight into the new government's approach to AI and the steps and potential timelines it intends to take for developing regulation and guidance, which many consider are needed to drive AI adoption. Instead, ministers are taking time to develop a strategic roadmap and approach to legislation.
"There is concern that over-regulation may restrict innovation as complex legislation requires resources to understand and implement it. That needs to be balanced against safety, fairness and trust when adopting AI. I would like the UK to avoid stifling innovation through knee-jerk regulation and learn from other parts of the world.
“In the energy sector, as in others, I think the key is to avoid a one-size-fits-all approach and instead focus on industry-specific AI regulation. This tailored strategy should enable organisations to rapidly close any gaps in adoption, and could see UK firms eventually lead the way.”
Caroline Churchill, Partner, Womble Bond Dickinson
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