Reasons For Optimism: Lessons From Day 1 Of The Emea Modular & Uk Large Reactors 2026 Conference

Rather to my surprise, I left day one of this year’s EMEA Modular & UK Large Reactors conference with a discernible spring in my step. Despite the windowless room and the watery coffee, there was undeniably a buzz of excitement arising from:

• Increased prioritization of nuclear energy by the European Parliament (including an important policy shift whereby nuclear energy projects are now eligible for EU funding) (Kristian Vigenin, member of the European Parliament)
• In light of the Fingleton Review, recognition from the UK Government that significant regulatory reforms are required to facilitate the provision of nuclear energy in this jurisdiction (Mustafa Latif-Aramesh Partner at TLT LLP and member of Nuclear Regulatory Taskforce, Sam Dumitrui of Britain Remade and Albert Yu of Orrick LLP)
• South Africa’s ambition to build on its existing nuclear infrastructure to lead the development of nuclear technologies across Africa (Nomso Kana of Office of the Eastern Cape Premier and Africa4Nuclear)
• Pitches from regulators around the world keen to showcase their professionalism and commitment to the sector (e.g. Federal Authority for Nuclear Regulation in the UAE and the Nigerian Nuclear Regulatory Authority)
• Investment in nuclear powered ships and ice-breakers (Steven Fox from Propeller Ventures).

For me though the highlight was the excellent talk from Kirsty Gogan of the non-profit Terra Praxis about how AI is helping to make the shift to nuclear a reality, along with the resulting environmental, economic and social benefits.

I had always understood that one of the key benefits of nuclear is that it is a high energy density solution. Kirsty provided an exceptionally powerful demonstration of this through a graphic showing the total area required to replace the UK’s current oil consumption with hydrogen if this were generated from wind (136,120km2), solar (26,090km2) or advanced heat sources (55km2). To put this in context, 136,120km2 equates roughly to the whole area of England! I struggle to see how anyone committed to the environment could not be a proponent of nuclear (safely and responsibly delivered of course), in light of these statistics.

Having set the scene in this way, Kirsty stressed that nuclear energy can only be delivered at the scale and pace required if the nuclear industry shifts from a “project-based” design to a “product-based” model. In other words, designs must be standardized rather than tailored to particular sites. Product-based licensing would then follow.

The hope is that existing brownfield energy sites would be converted to nuclear using the above model which would minimise environmental damage and reinvigorate the relevant communities with cutting-edge jobs and the resulting social benefits. The efficiencies and benefits would be further maximized by co-locating high energy uses, such as data centres, at the sites in question.

Fortunately AI tools are helping to make the vision above a reality by screening and selecting sites, and then generating instantly site-specific reactor configurations and deployable design specifications. For example, 13 priority sites in Ukraine were screened and configured in a matter of days when such a process would typically take years.

Microsoft (with input from others including Terra Praxis) have been developing tools which automate the production of licensing applications in the USA by reference to the regulatory requirements in that jurisdiction. To give a concrete example of the resulting reduction in time (and therefore cost), Aalo Atomics has recently reported a 92% reduction in permit timeline using these tools.

As a lawyer who works in the nuclear sector, should I be alarmed? No, I don’t think so, and neither does Kirsty. Expert legal input will still be required both in helping to develop these tools but also in respect of individual applications. The hope, however, is that the legal input can be focused on the difficult issues rather than the generic or mundane. And speaking of difficult issues, a particularly thorny one remains with regards to how the waste from these new technologies can be satisfactorily disposed of. Perhaps AI will provide the solution here too, but it has not done so yet.