Digital transformation: AI’s role in the energy transition

At a recent Innovation Forum webinar, experts from across the energy system discussed how digitalisation and artificial intelligence are being applied in practice – and where expectations may be running ahead of reality. Panellists from energy networks, renewable project development and digital consultancy explored how AI is already delivering tangible value, particularly in grid management and project delivery, but also highlighted the structural, cultural and governance challenges that will shape its long-term impact.

Digitalisation is no longer viewed as a marginal efficiency tool. For many energy companies, it is becoming central to how complex systems are planned, operated and optimised. Participants agreed that AI’s real value lies not in replacing existing processes, but in accelerating them – enabling organisations to handle greater volumes of data, model more scenarios and make decisions faster under uncertainty.

A recurring theme was the growing tension between rising electricity demand – particularly from data centres and digital infrastructure – and the physical limits of existing grids. While AI is often framed as part of the demand problem, panellists argued it could also be part of the solution, enabling smarter forecasting, real-time system optimisation and better coordination between generation and consumption.

Existing infrastructure

One of the most immediate use cases for AI is in maximising the performance of existing assets. Rather than relying solely on costly network build-out, system operators are increasingly using machine learning to extract more capacity from current infrastructure.

Dynamic line rating, for example, allows transmission operators to adjust line capacity in real time based on environmental conditions, increasing throughput without compromising safety. When deployed at scale, such approaches can unlock significant additional capacity while deferring the need for new physical infrastructure.

More broadly, improved system modelling and demand forecasting are enabling better spatial planning – helping local authorities, developers and network operators understand where new connections are feasible and where constraints are likely to emerge.

Accelerating development

For project developers, AI is being used less as a headline technology and more as a productivity tool. Webinar panellists highlighted how digital tools are shortening development cycles by automating site screening, speeding up compliance processes and enabling rapid scenario analysis.

What previously took teams several days or weeks – such as early-stage site suitability assessments or design optimisation – can now be completed in minutes. This creates a competitive advantage in increasingly crowded markets, while also helping companies scale their development pipelines without proportional increases in headcount.

However, participants stressed that AI should be treated as an accelerator, not a substitute for professional expertise. Human judgement remains critical, particularly in regulatory engagement, environmental assessment and financial decision-making.

System resilience

Beyond development, AI is also being deployed to strengthen operational resilience. Predictive maintenance, weather forecasting and automated system responses are helping operators protect assets from extreme events and reduce downtime.

Examples highlighted during the webinar included the use of machine learning to adjust solar panel positioning ahead of hailstorms, and the deployment of cloud cameras and real-time forecasting tools to provide grid operators with more accurate short-term generation data.

These applications not only protect individual assets, but also contribute to wider system stability – improving the ability of grids to manage intermittency and balance supply and demand.

Tech limits

Despite endorsing the potential from technology, panellists were clear that technology alone cannot solve structural system challenges. One recurring concern was the risk of fragmented infrastructure development, particularly if large energy users such as data centres turn to private generation and off-grid solutions.

Without coordinated industrial strategy and regulatory alignment, there is a risk that AI-driven demand growth could undermine grid stability, create security risks and increase inequality in energy access.

Similarly, participants highlighted that digital transformation often fails when treated purely as an IT project. Successful adoption depends on organisational culture, incentives and governance – including retraining staff, redesigning workflows and embedding AI into decision-making structures.

Governance and oversight

A further challenge is the lack of shared standards. While companies are investing heavily in proprietary systems, the absence of common data structures and industry frameworks risks duplication, fragmentation and inefficient learning.

Several panellists argued that shared assumptions, open collaboration and sector-wide learning could unlock far greater value than isolated innovation efforts.

Crucially, all agreed on the importance of maintaining human oversight. AI may assist with optimisation and analysis, but responsibility for critical decisions – particularly in trading, compliance and system safety – must remain with people.

What’s next?

The discussion highlighted that AI’s role in the energy transition is neither revolutionary nor trivial. Its real impact lies in making existing systems work better: accelerating deployment, improving coordination and enabling more adaptive planning.

However, without aligned policy, organisational change and shared standards, digitalisation risks becoming another layer of complexity rather than a driver of resilience.

As energy systems face rising demand, infrastructure constraints and increasing climate volatility, the challenge is not simply to deploy smarter tools – but to redesign how technology, people and institutions work together to manage a far more complex transition.

For the full webinar recording click here.

These themes will be explored further at the Energy Transition Innovation Forum, taking place in Amsterdam on 15–16 April 2026, where senior leaders from across the energy system will convene to examine how digitalisation, investment and system design can support a more resilient and competitive transition.