By Guillaume Eymery, Chief Strategy Innovation & Digital Officer at Nexans
The global push toward decarbonisation is accelerating a seismic transformation across the electrification industry. As nations race to overhaul ageing grids, scale renewable energy and deploy electrified technologies across homes, transport and industry, the systems underpinning our energy supply are becoming more complex than ever before. At the same time, artificial intelligence (AI) is maturing at an unprecedented pace, reshaping how organisations understand risk, design infrastructure and manage vast networks of physical and digital assets.
The rapid evolution of electrification and software intelligence are now tightly intertwined. The more electrified our world becomes, the greater the need for automation, data-driven management and predictive insight. As AI evolves, it has the potential to become capable not only of processing this complexity but of transforming it into strategic advantage.
For business leaders navigating this new era, AI represents a structural change rather than a technological upgrade. It affects engineering workflows, maintenance strategies, safety culture and even the resilience of critical national infrastructure. Understanding its impact is essential for building the reliable, secure and sustainable energy systems the future demands.
AI Accelerates Innovation and Performance
Innovation in the electrification sector has traditionally been dominated by incremental improvements to materials, components and design processes. But AI is rapidly redefining the pace and possibility of that innovation. Advanced algorithms can ingest and analyse engineering archives, testing parameters and environmental datasets that would take human teams years to evaluate. By generating millions of design variations and simulating their performance, AI helps engineers uncover solutions that are more resilient, more sustainable and more cost-effective before any physical prototypes are created.
This shift is influencing how products such as cables, connectors, switching systems and renewable-energy components are conceived. AI-assisted design tools are supporting the development of assets that are fundamental to energy transition, such as fire-resistant materials, lighter and more flexible components, and products that are easier to recycle. The ability to evaluate trade-offs between durability, efficiency, environmental impact and cost at the earliest stage is accelerating time-to-market and expanding the scope of innovation.
AI’s influence reaches far beyond product development. Electrification systems generate enormous amounts of operational data. These include sensor readings, environmental measurements, maintenance logs and performance histories, and they provide a rich foundation for improving reliability. AI can detect anomalies within these datasets that human operators would be unable to, especially at scale. By learning from patterns within equipment behaviour, environmental conditions and historical failures, AI can predict when components are likely to degrade or malfunction. The result is maintenance that is proactive rather than reactive[1], reducing unplanned downtime and extending the life of essential infrastructure[2].
For grid operators, AI offers an additional layer of intelligence that enhances the overall stability of the system. By combining weather forecasts, load data and real-time equipment performance, AI can anticipate demand spikes, identify stress points on the network and adjust the flow of power to maintain balance. This level of automation is particularly valuable as renewable-generation assets grow and the grid becomes more dynamic. With solar, wind and storage technologies introducing greater variability, AI provides the analytical capability needed to orchestrate power flows efficiently and sustainably.
AI Safeguards People and Infrastructure
While innovation and performance are key drivers, safety remains the foundation of every electrification environment. Factories, substations, renewable-energy farms and cable manufacturing sites all carry inherent risks, from high-voltage equipment to heavy machinery and complex operational workflows. AI is emerging as a valuable ally in identifying and mitigating these risks before they become incidents. By examining historical safety records, near-miss data and real-time operational inputs, AI can detect subtle signals that may indicate unsafe behaviours, equipment anomalies or environmental hazards. These insights help organisations intervene early, strengthening their safety culture and reducing the likelihood of accidents.
In global operations, where teams may speak multiple languages and work across different regulatory frameworks, AI also plays a role in harmonising safety communication. Automated translation tools and intelligence-driven reporting systems ensure that critical information remains accessible and consistent across regions, reducing the risk of misinterpretation.
Beyond the boundaries of industrial sites, AI contributes to the protection of critical national infrastructure. Electrical grids, renewable-energy installations and underground cable networks face growing threats, primarily from extreme weather, ageing components and cyberattacks. Continuous monitoring powered by AI enables operators to identify unusual patterns in asset behaviour, shifts in environmental conditions or early signs of physical strain. These insights can support targeted repairs, asset replacement programmes and resilience planning, ultimately helping prevent large-scale outages.
AI also strengthens the digital defences of increasingly connected energy systems. As smart grids expand, the attack surface for cyber threats widens. AI-driven security tools can detect unusual or suspicious network activity, identify vulnerabilities and respond to anomalies with a speed far beyond manual capabilities. This level of vigilance is essential as the industry becomes more digitised and interdependent.
Repurposing Human Expertise and Data Quality
Although AI is reshaping the electrification landscape, its effectiveness depends on two critical factors: human expertise and high-quality data. Electrification organisations generate vast amounts of information across their operations, yet this data is often fragmented, outdated or locked away in isolated systems. Without structured, accurate and consistently maintained data, AI models cannot perform reliably. Many organisations are beginning to invest heavily in data governance, standardisation and cleansing to ensure that their AI-driven insights are trustworthy and actionable.
The true value of AI emerges only when human expertise is integrated into its use. Engineers, planners, analysts and frontline operators bring essential context, judgement and ethical oversight that ensure AI outputs are interpreted correctly and applied responsibly. This partnership is what enables organisations to make decisions that align with safety, sustainability and operational priorities.
As the energy transition accelerates, collaboration between people and advanced technology, including AI, will shape the future of electrification. The organisations that thrive will be those that combine advanced intelligence with deep domain knowledge, creating systems that are safer and more resilient.
[1] Establishing the right analytics-based maintenance strategy
