Artificial intelligence and other emerging technologies have a potentially huge role to play in successfully meeting the UK’s various energy challenges. Indeed, such platforms will be vital in upgrading and decarbonising the UK’s energy system, meeting growing energy demand, ensuring security of supply and keeping prices down for consumers.
However, as these technologies are introduced across the energy system, it is crucial that the government works closely with the industry to reap the benefits while mitigating the risks.
Energy infrastructure outages can have widespread and serious consequences for both individuals and society. As well as the impact of physical damage to infrastructure, such as the recent substation fire that saw the closure of Heathrow airport, energy infrastructure vulnerability to AI misinformation and cyber attacks is rapidly becoming one of the biggest threats to the UK – one that the government must take steps to minimise.
The economic impact of an electricity blackout depends on factors such as duration, geographic impact and affected sectors. Estimates suggest that a nationwide blackout lasting 24 hours could cost billions of pounds. These are not just hypothetical scenarios; a Vorboss report published in April 2024 found that the UK economy suffered a loss of £17.6bn in economic output due to connectivity outages in the preceding 12 months, with the average UK business losing out on over £11,000 in economic output.
These were relatively short power outages. But if a system blackout lasts more than a few days, the economic damage could reach tens of billions of pounds, leading to supply chain failures, impacting hospitals and emergency services, seeing mass business closures and causing potential social unrest. Government investment in cyber security and network resilience today can save billions in lost revenue tomorrow.
The increasing number of devices connected by digital networks, including in energy infrastructure, also exposes these areas to new risks. If systems are fed with incorrect or misleading information, they might fail to identify potential issues such as impending equipment failures or capacity shortages.
Misinformation is often a tool used by cyber attackers who want to disrupt grid operations. AI-driven malicious misinformation campaigns can mislead operators or automated systems, causing disruptions and outages. An AI system manipulated by false data could also expose vulnerabilities for hackers to exploit, resulting in a third-party taking control of critical infrastructure, disrupting operations, or gathering confidential information.
To mitigate these risks, effective cybersecurity measures and training for all staff are essential to protect systems from manipulation. Workers will need differing levels of understanding of, and training on, AI depending on their organisational roles.
It is crucial to ensure that any AI systems deployed are robust, transparent, and subject to comprehensive validation and verification processes. There should be tools and techniques that are available to AI developers that can help them prove they are safe and fit for purpose to regulators, with competency frameworks and lists of recognised qualifications to help provide organisational reassurance over developer competence in particular areas.
There is a challenge finding people with the required skills at competitive salary rates. The Growth and Skills Levy should ensure flexible funding, particularly for SMEs, to upskill existing workers with bespoke short courses (microcredentials). This would help ensure a basic standard of safety and competency for those at “working” and “practitioner” level. At the higher “expert” level, key cyber security roles should have protected status (in the same way as “medical doctor”) to help drive up and guarantee standards.
While the integration of new technologies such as AI into our energy infrastructure systems poses threats, there are also significant security benefits to be gained from harnessing them safely.
For example, by integrating AI alongside the adoption of cyber-physical systems like “digital twins” – virtual models connected to a real-world counterpart by a two-way flow of real-time data – we can monitor and rapidly address faults, boosting security and resilience. This is already being adopted on a case-by-case basis, but the potential benefits from a whole systems approach is game-changing.
If the government coordinates the energy industry to bring together the different digital twins of critical energy infrastructure into one holistic model, this could then be used to monitor and address issues across the whole system. By joining up monitoring and intervention of generation, transmission and consumption, government can ensure a secure supply of energy across the country.
But we cannot realise the potential of these technologies without the skilled workforce to utilise and adopt them. UK engineering and technology firms are the least likely to recognise digital twins as a priority for reaching net zero (5 per cent), and fewer than a quarter of employers think that we have the skills in this area, which include data collection and analysis.
The introduction of AI into the systems that control our energy infrastructure is already underway. This brings both the potential to strengthen security and resilience through innovation and the risk of a system failure – either through unintentional failures or from the ongoing efforts of malicious actors to access and weaken our systems. The best way to reap the benefits of new technologies and mitigate the risks is to ensure that all workers are given appropriate training on the safe and effective use of AI and digital systems, along with investment in cyber security expertise and robust regulation.
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