3 things leaders must know about AI for structural integrity and how it will help the energy transition

Rising energy demand, aged energy infrastructure, volatile markets and the largest infrastructure investment challenge in history. This is the backdrop to the World Economic Forum Annual Meeting 2026 in Davos, Switzerland, even as the journey towards a just energy transition becomes critical.

However, the ability to decarbonize without deindustrializing will determine who closes the $6 trillion annual infrastructure gap and who falls behind.

While countries race to build new renewable capacity, modernize assets and secure supply chains, a massive infrastructure shortfall besets the global system. This has begged the question: how do we create more value and lower emissions from existing operational infrastructure – safely, efficiently and at scale – while constructing systems of the future?

One unexpected answer lies in steel, where a new class of intelligence, physics-based artificial intelligence (AI) for structural integrity is emerging.

This technology uses data analysis and machine learning to give operators a real-time understanding of how their assets actually behave: their true condition, remaining life and safe operating limits to discern the health of their assets. These insights are now shaping decisions on performance, safety and resilience across entire sites and industrial clusters.

This year, the World Economic Forum’s Global Lighthouse Network recognized AI for structural integrity as a distinct technology of the fourth industrial revolution, signalling its global scaling and reshaping how industries operate.

AI for structural integrity’s role in the energy transition

There are three things every leader should know about this trend and its role in the energy transition to stay competitive in the year ahead.

For decades, industrial systems could monitor flows, pressures and temperatures but not the condition of the steel structures that hold facilities together. This “invisible system” is where many disruptions originate.

In refinery facilities, the majority of physical assets comprise static, pressurized steel equipment such as pressure vessels, columns, piping and storage tanks, which represent the bulk of installed plant infrastructure outside of rotating machinery.

The result is unplanned downtime costing billions – hundreds of millions spent on unnecessary inspections and maintenance, and premature asset replacements that drive a significant carbon footprint – outcomes no business wants.

Physics-based AI reveals how structures actually behave under real operating conditions, giving operators live visibility into structural health, true capacity and safe operating limits.

The result is a shift from reactive maintenance to real-time decision-making that improves performance, extends asset life and optimises operating envelopes, already proven across major industrial sites worldwide, as deployment of Akselos technology case studies show.

At a major European refinery, operators identified more than $150 million in annual value by safely expanding operating envelopes, extending catalyst life and reducing future capital spending.

At a large downstream plant in the Middle East, structural intelligence generated more than $400 million in value – over $170 million in deferred capital expenditure, over $125 million in operating expenses savings and over $100 million in potential revenue uplift.

At an offshore site, inspection costs were cut by one-third and structural life increased by over a decade, unlocking hundreds of millions in value.

The value compounds with scale. It took eight years to secure the first $1 billion in industrial assets, three more to reach $10 billion and just two to surpass $100 billion. This accelerating curve makes the coming year critical – companies that don’t grasp this technology risk falling behind.

The energy transition requires industrial infrastructure to become more flexible aswell as harness efficiency gains. The rise in green molecules can help.

When a plant changes its feedstock, such as shifting crude slats, introducing bio-feedstocks or co-processing hydrogen, the equipment begins operating outside its original design window. Operating conditions shift, placing new demands on structural performance.

This is where AI for structural integrity becomes an essential enabler, allowing operators to adapt safely while maintaining productivity and reliability.

This flexibility is becoming a significant measure of competitiveness. As one energy leader noted during the Forum’s Europe energy cluster discussions at the meeting titled, Radical Collaboration: Role of Data and Digital in Accelerating Innovation in Industrial Cluster Ecosystems, “There is no benefit to low-carbon energy if it comes at the cost of our industrial base.”

Industrial clusters across Europe are demonstrating how shared intelligence can accelerate the transition. In Rotterdam, Antwerp-Bruges, the Humber and other regions, companies are integrating hydrogen systems, circular carbon solutions, and carbon capture, utilization and storage into coordinated industrial ecosystems.

When trusted data and insights flow across these systems, including refineries, power producers, ports and transport networks, performance improves and emissions fall. Entire regions become more competitive as a result.

In this next phase of the energy transition, flexibility becomes a strategy and intelligence becomes infrastructure.

The next five years will be defined by scaling what already works, strengthening what exists and deploying new systems without disrupting those we currently rely on. Given the scale of global energy demand, fully replacing large industrial assets is unfeasible.

Reinvention will, therefore, drive the transition. Companies will need to extend the operating envelope and structural life of existing assets, not rebuild them. They will need to use new technologies to safely manage new fuels and operate in connected, real-time industrial clusters. And resilience will need to be integrated directly into planning and permitting.

We see this already in liquefied natural gas, where operators are using structural intelligence to unlock €200 million in estimated structural value by extending vaporizer lifespans, increasing throughput within safe operating limits and deferring large replacement programmes by understanding the true condition and capacity of existing assets.

AI for structural integrity can play a role in this reinvention, helping accelerate decarbonization in a safer, more affordable way. It also provides a preview of the next phase of the fourth industrial revolution. Progress will come from deployment at scale, across sites, clusters and entire systems.

As leaders gather this January, they will be discussing how the global energy conversation has shifted from ambition to execution, from commitments to capability. The transition must now deliver industrial resilience, economic value and climate progress simultaneously.

AI for structural integrity is one example of how that quietly happens.

The energy sector is now seeing this trend enable industries to enhance asset performance, extend asset life, reduce downtime, integrate new fuels safely and operate with greater flexibility. When implemented across industrial clusters, it allows entire regions to become more competitive while accelerating decarbonization.

The energy transition will not be won by replacement but by reinvention, beginning with understanding the physical systems that underpin our economies.