Artificial intelligence is becoming an increasingly important tool across the power sector. While much of the conversation has focused on future possibilities, many organisations are already using AI to improve manufacturing efficiency, strengthen quality assurance and support more informed asset management decisions.

For utilities facing unprecedented investment in grid infrastructure, and for manufacturers working to increase production while maintaining quality, AI is emerging as a practical technology that can help reduce risk and improve performance across the transformer lifecycle. 

AI is moving from experimentation to practical application 

For several years, AI was often discussed as a future capability with significant potential but limited real-world application. That picture is beginning to change. 

Across manufacturing and grid operations, organisations are deploying AI to solve specific challenges rather than simply adopting technology for its own sake. Instead of replacing engineering expertise, AI is supporting engineers by analysing large volumes of operational data, identifying patterns and helping teams make faster, more informed decisions. 

This shift is particularly important for the transformer industry, where increasing demand is placing greater pressure on manufacturing, procurement and asset management. 

Improving manufacturing efficiency 

One of the earliest areas where AI is delivering measurable value is within manufacturing operations. 

Modern production facilities generate vast amounts of data throughout design, manufacturing and testing. AI can analyse this information to identify trends, optimise production schedules and highlight potential quality issues before they affect finished products. 

Combined with automation and digital manufacturing systems, these capabilities allow manufacturers to improve consistency while making better use of available production capacity. 

This is particularly valuable at a time when transformer manufacturers are balancing growing order books with continued constraints around skilled labour and testing resources. 

Rather than replacing experienced engineers, AI enables them to focus on higher-value technical decisions by reducing the time spent analysing routine production data. 

Supporting smarter asset management 

Utilities are also finding practical applications for AI beyond the factory. 

Modern transformers increasingly generate operational data through online monitoring systems, embedded sensors and condition monitoring technologies. AI can analyse this information alongside historical performance data to identify patterns that may indicate developing faults or changes in asset condition. 

These insights support maintenance planning by helping operators prioritise inspections, allocate resources more effectively and reduce the likelihood of unexpected equipment failures. 

For organisations managing large transformer fleets, this approach supports more informed asset management while improving network reliability and reducing lifecycle costs. 

Better decisions require better data 

Despite its potential, AI is only as effective as the information it receives. 

High-quality operational data, consistent asset records and strong engineering knowledge remain essential. AI should be viewed as a decision-support tool rather than a replacement for technical expertise. 

Successful organisations are combining digital technologies with decades of engineering experience, ensuring that AI complements existing processes rather than introducing unnecessary complexity. 

This balanced approach allows organisations to build confidence while delivering practical operational improvements. 

Looking ahead 

As Europe's electricity networks continue to expand, AI is likely to play an increasingly important role in supporting transformer manufacturing, improving asset performance and strengthening grid resilience. While the technology will continue to evolve, its greatest value lies in helping organisations make better decisions, improve efficiency and reduce delivery risk across the entire value chain. 

For utilities, manufacturers and suppliers alike, the future of AI is not about replacing people. It is about giving experienced teams better information to plan, manufacture and manage the infrastructure that underpins Europe's energy system. 

Join utilities, TSOs, DSOs, transformer manufacturers and digital technology leaders at CWIEME Berlin's Grid Delivery Summit to explore how AI, advanced analytics and digital manufacturing are helping deliver smarter, more resilient electricity networks.