By Núria Agell
Artificial intelligence (AI) is delivering a major technological breakthrough this century. In the energy sector and other areas of business, it is massively changing how organisations operate. It also offers new opportunities to improve efficiency and energy sustainability.
But while AI is accelerating, many organisations are still building the capability to apply it confidently in real energy-system contexts. This creates a clear market gap. Exactly the kind of gap initiatives like AI4GreenDeal are designed to address through targeted AI and data skills development.
This shift also brings economic and environmental risks. In the article below, three positive examples are identified, followed by two areas where decision-makers need to proceed with care.
Improved forecasting and planning:
AI improves the ability to predict both energy demand and renewable energy production. This leads to a considerable reduction in decision-making uncertainty. By analysing weather and consumption data, and by using AI-based forecasting systems, companies can better plan energy production and distribution.
A well-known example is Google DeepMind’s collaboration with electricity grid operators to predict wind energy generation. This partnership improved grid stability and optimised resource utilisation.
Operational optimisation and risk reduction:
A key positive impact of AI is operational optimisation and the reduction of technical risks through predictive maintenance. For example, AI algorithms can detect anomalies way before serious failures occur. This enables more efficient decision-making and faster responses.
Companies such as Siemens Energy use AI systems to monitor turbines and infrastructure. This decreases operational costs and avoids supply disruptions.
Support for strategic decision-making and sustainability:
AI also aids long-term strategic decision-making, especially in the context of the energy transition. Using simulations and scenario analysis, companies can assess investments while also evaluating risks and environmental impacts.
Companies such as Shell and BP, for example, apply AI models used to assess renewable energy investments. These models are also used to explore emissions-reduction strategies.
Technological dependence and potential decision-making errors:
AI can strengthen decision-making, but it works best when paired with strong human monitoring. Excessive dependence can reduce checks and balances. These errors in data or algorithms may result in considerable economic consequences. In some electricity markets, automated energy trading systems have caused unexpected price fluctuations. This is a reminder of the value and importance of human supervision.
High energy consumption of AI and lack of regulation:
Widespread AI use involves high energy consumption linked to data centres, which must be maintained at low temperatures. Platforms such as Amazon Web Services, Microsoft Azure, and Google Cloud operate infrastructures that consume large amounts of energy. The regulation on their environmental impact remains limited. As a result, the focus is increasingly on how to manage this footprint responsibly. This includes investments in future solutions such as nuclear-powered systems. By doing this, the anticipated instability in electricity grids can be mitigated through public infrastructure. Microsoft and Amazon are examples in this regard.
How can we better support the green and digital transitions using AI?
In the energy sector, artificial intelligence is redefining business decision-making and delivering significant benefits. However, due to its high energy consumption, new risks have been introduced. Responsible implementation (supported by appropriate regulations and human oversight) is essential to ensure a positive, sustainable impact.
AI4GreenDeal supports both green and digital transitions by training advanced AI and data professionals for sustainable energy systems. In collaboration with 10 countries, the initiative will deliver a 120-ECTS double-degree Master’s programme and 238 hours of flexible, stackable online modules. These efforts aim to strengthen the talent pipeline required to translate AI ambitions into safe, practical applications within sustainable energy systems.
Núria Agell is a Full Professor in the Department of Operations, Innovation and Data Sciences at Esade Business School. She holds a PhD in Applied Mathematics from UPC-BarcelonaTech. She served as Director of Esade’s Department of Operations, Innovation and Data Science from 2015 to 2023, and previously directed Esade’s PhD programme and Master of Research in Management Sciences from 2005 to 2013. A former President of the Catalan Association for Artificial Intelligence (ACIA), her research focuses on AI techniques and decision-making systems, including learning algorithms, qualitative and fuzzy reasoning, and multi-criteria and group decision-making.
AI4GreenDeal is co-funded by the European Union under the DIGITAL programme, supporting Europe’s strategic priorities in advanced digital education, innovation and the green transition.