Over the last few years, the UK’s critical national infrastructure has been put under unprecedented pressure. Geopolitical tensions and wars, such as those in Ukraine and Iran, have been significantly disruptive. They have inflated energy costs and weaponized supply chains. We’ve seen an increase in cybersecurity risks against critical infrastructure. Markets and demand have also become more volatile, with sudden price spikes and variations shifting energy procurement plans at the same time as the UK is in a race to net zero. But this rapidly increased move toward renewable energy production and usage — while also aiming to reduce the UK’s long-term reliance on imported oil and gas — puts pressure on power infrastructure that has been designed for different operating models. This is because grid cycling between energy sources is necessary today, as the UK strives to keep its lights on. However, this approach is not without challenges as equipment is stretched and damaged over time. Yet the UK must extend the life of its critical national infrastructure somehow.Grid Cycling Places UK Infrastructure Under StressUK power plants were originally designed to run at a steady state. However, today’s operations have created a completely new picture. The power infrastructure’s new standard operating procedures result in the cycling of gas (thermal stations), solar and wind depending on demand, with systems repeatedly being turned on and off again.Consequently, energy infrastructure is degrading at an unforeseen rate due to changes in stress, fatigue and creep, among other things. While energy cycling is essential to maintain grid stability, it is, in many cases, putting pressure on plants already operating far beyond planned lifespans.Therefore, the UK’s critical infrastructure faces mounting maintenance and longevity challenges. Operators need to find a way to extend its life — including nuclear power — while also managing the demands on energy and components. Furthermore, since weather-dependent energy sources are inherently unpredictable, frequent grid cycling creates new stress regimes on equipment and accelerates damage to assets. Solving part of this problem requires more effective, reliable real-time monitoring that informs the maintenance of key components within power plants and infrastructure.Meeting Tomorrow's Energy DemandsAcross the globe, accelerating net-zero targets have become a priority too. With countries looking to improve energy security and sustainability, local, clean power generation has become popular. The UK is making progress here. For example, one target is for all electricity to come from 100% zero-carbon generation by 2035. In May 2026, 65% of electricity was generated by zero-carbon sources.Although, in addition to wind and solar-generated power, the UK remains reliant on its legacy nuclear and thermal (gas) plants. However, this exposes a challenge: New operating patterns designed to support grid flexibility and renewable integration create new stress regimes and accelerate asset damage. Assets that were designed to operate steadily for decades are now repeatedly starting, stopping and ramping output to balance an increasingly dynamic energy mix. While improving UK energy security is a critical aspect of energy production, the implications for infrastructure reliability, resilience and longevity are severe.Unpredictable asset deterioration across power stations and related infrastructure not only compromises operational performance but also raises new safety concerns. As such, operators need better visibility into how assets are aging and degrading. They need capabilities to recalibrate maintenance models based on accurate asset life consumption. Better data and insights can help.Expensive Four-Year Inspection Cycles and SimulationsThis new era of grid cycling has called into question traditional repair and replacement cycles across the power generation sector too. Traditionally, and still today, much of the industry runs a four-year manual inspection cycle of equipment. During inspections, power stations are off line for eight weeks or more while inspection, repair and replacement take place. Increasing the frequency of these would be unaffordable and costly to operators. After all, this process temporarily removes the plant’s generation capacity from the market and requires grid operators to reroute power, meaning that these inspections also directly impact grid ranking.However, increasing the frequency of inspections isn’t the solution operators are looking for either. Additionally, simulations traditionally used to help determine asset degradation no longer reflect today’s rapid grid cycling operating model. Previously, when plants ran unchanged for a long time, a subset of data used for simulation was representative of the entire production span. However, this is no longer sufficient or reliable when the unpredictability of power demand creates enormous fluctuations. Furthermore, this approach is quite expensive to run for operators. Instead, a new cost-effective methodology using physics-informed neural networks (PINN), can deliver engineering-grade accurate insights and results fast enough for strategic real-time decisions to be made.What is compelling here is that the industrial data needed to support PINN and physics-based artificial intelligence is available. Operators have an array of data that optimizes operational performance. Temperature, pressure and operating history data are routinely collected. Converting this info into real-time engineering intelligence enables operators to transform how they monitor and manage critical infrastructure.Asset Management Strategies Based on Actual Condition – Not Perceived RiskMoreover, by combining engineering-grade, physics-based AI with real-time operating data, operators can gain a continuous assessment of asset condition, including stress, damage accumulation and life intelligence. This immediate visibility into degradation trends enables maintenance and replacement decisions to be based on measured asset behavior rather than assumed performance.Managing assets according to their actual condition rather than a perceived risk of failure not only reduces the likelihood of unplanned outages but also helps operators control maintenance costs. Understanding how frequent grid cycling affects different asset types in real time — potentially at not just one power station but across multiple sites — will enable operators to adopt an intelligence-led approach to asset management that will avoid unnecessary repairs and replacements. This, in turn, will reduce the total life cost of each asset while reinforcing safety protocols.Rather than treating asset health as a separate maintenance consideration, continuous monitoring allows degradation and performance data to become part of day-to-day operational planning. The insights generated can shape replacement strategies and even inform future plant design. Perhaps most importantly, it will allow operators to determine how best to extend the life of the plant.ConclusionThe UK’s critical national infrastructure has been operating under significant pressure for a long time, even before geopolitical conflicts created additional fluctuations in the cost and availability of oil and gas. Many existing assets are now operating well beyond their original design life. Additionally, as the UK and Europe continue their transition toward net zero, thermal generation will increasingly be called upon to operate flexibly, leading to more frequent load cycling, accelerating asset degradation.Balancing resilience, efficiency, safety and asset longevity has therefore become one of the industry’s greatest operational challenges. Achieving this balance will require a far deeper understanding of how degradation is evolving under operating conditions, enabling assets to be managed according to their actual condition throughout their service life, rather than historic assumptions.This is where physics-based AI, combined with existing operational data, can transform asset management. By providing continuous insight into changing operating patterns and their impact on degradation, repair, maintenance and replacement, upkeep strategies can be developed based on actual damage and condition instead of expected damage. Ultimately, continuous monitoring gives operators the confidence to make better operational decisions. This supports a more secure, flexible energy system while safely extending the life of the critical infrastructure it depends on.Benedikt Engel is the CEO and cofounder of MatAlytics, a UK deep-tech software company originating from research at the University of Nottingham. The views expressed in this article are those of the author.