It’s fair to say that AI feels more like a utility than a single technology. It’s an invention that will change all aspects of our lives, bearing a close resemblance to the mass adoption of other utilities in history, such as electricity.
The UK today has a lot to learn from the electrification period. Our lightbulb moment was the Electricity (Supply) Act 1926, which set out a vision for a unified national grid. Policymakers realised that a fragmented patchwork of local power systems would never be able to serve a modernising nation. Standardisation was mandated, which led to unified voltage levels, synchronised frequency, and the creation of our excellent and ubiquitous three-pin plug. Britain was a trailblazer. Unification drove economic growth.
We are now adding another layer to the system: AI and information processing. This layer sits between human decision-makers and collected data; an intelligent interface that can monitor and operate processes. The possibilities are enormous for all industries, perhaps none more so than the energy sector. With the Climate Change Committee estimating electricity usage to double by 2050, optimising these systems is becoming increasingly important.
Today, in the advent of another technological revolution, standardisation offers a valuable opportunity. While exciting innovation is taking place across the sector, efforts are still unfortunately fragmented and siloed. If all our energy companies rally around a shared vision for AI adoption, one with common models, data sharing protocols, and APIs, maybe Britain could become a trailblazer again.
Why does this matter? According to privacy expert Proton, 88 per cent of publicly listed companies in the UK are reliant on US-based technology. This might not be surprising, given America’s longstanding leadership in technology, but it still feels significant. In a world of conflict and shifting alliances, technological reliance on other nations can be a strategic vulnerability. At its most innocuous, it complicates domestic private sector regulation and limits diplomatic flexibility; at worst, it creates a form of digital dependence. Our overreliance isn’t confined to corporations either – consider Palantir’s role in the NHS since the pandemic or the data being captured in schools by Google Classroom.
The good news is that when it comes to energy, we’re well-placed to standardise in order to reclaim our AI sovereignty. Thanks to that same 1926 Act, our electricity network still has remarkable conformity to build upon. Many of our physical assets are standardised, meaning defects and problems are consistent; most Distribution Network Operators (DNOs) operate the same version of the Distribution Code, which is approved by a centralised regulator (Ofgem); The Electricity Act 1947 concentrated more than 600 local institutions into standardised Area Electricity Boards; and our voltage and wattage levels are broadly consistent across the same 400 kV and 275 kV lines (and 132 kV lines in Scotland). This standardisation makes building uniform technologies easier, be that shorter development and testing loops or reduced integration complexity when solutions are ready to be rolled out.
While our energy companies have made diligent strides through some highly innovative, Ofgem-backed projects, such as UK Power Networks’ Wayl-Ease data platform and initiatives by SSE and National Grid Distribution to open their data up for public use, there’s still room for greater coordination across the sector. Currently, technological and AI approaches remain fragmented, which can result in duplicated effort, unnecessary costs, and missing out on the economies of scale that come with applying AI to large, shared datasets.
The untapped potential is enormous. Computer vision can monitor transmission tower corrosion more easily, enabling predictive rather than reactive maintenance. This doubles the lifespan of towers, allows companies to spot corrosion much earlier, and frees up significant human labour. These technologies only improve with scale: a uniform, pan-industry approach would generate data, which leads to better tech, which leads to greater efficiencies. Saving just a single minute per tower inspection across the UK’s 50,000 transmission towers could recoup £1.65m. These cost savings would ultimately pass down to British consumers.
Standardisation can transform entire industries. When the aviation sector unified its air traffic control systems throughout the 50s and 60s, there was a wellspring of innovation and efficiency. Air travel became safer and faster, weather and disturbance data were shared globally, and technological evolutions emerged, like satellite use replacing radar, and digital communications replacing radio.
This is a timely and exciting parallel for Britain’s energy sector. A uniform technology and AI framework with common data standards, APIs, and based around shared models would bring significant efficiencies for energy providers, distributors, and transmitters. It would save consumers money, spark invention, and strengthen the UK’s position on the global stage. Achieving this won’t be simple and will require companies to work together and establish new frameworks for data sharing. But in a fraught world in the midst of a technological revolution, it would allow Britain to lead from the front.
Amjad Karim, CEO and founder of Keen AI