As Europe confronts significant economic challenges, the pursuit of both digital and green transitions has taken center stage in policy discussions.

The digital transition aims to capitalize on technology, particularly artificial intelligence (AI), to enhance productivity, while the green transition focuses on decreasing carbon emissions and transitioning to sustainable energy sources.

The burgeoning demand for electricity in both domains has raised concerns regarding potential conflicts between these objectives.

Artificial intelligence is recognized as a considerable factor in increasing electricity demand due to its dependence on data centers.

For instance, a standard Google search utilizes approximately 0.3 watt-hours (Wh) of electricity—the equivalent energy needed to power a 60W light bulb for around 20 seconds.

In contrast, AI-driven queries, such as those processed by systems like ChatGPT, can consume between 3 and 9 watt-hours per request, representing an increase of 10 to 300 times in energy consumption.

In the European Union, the electricity demands placed on data centers are already substantial.

By 2023, data centers accounted for about 21% of Ireland's total electricity usage, surpassing the combined total consumption of all urban households.

With the continued proliferation of data-intensive technologies and anticipated increases in battery electric vehicles and heat pumps, projections indicate that energy demand will further escalate, placing additional strain on already limited electricity supplies.

The pressing need to enhance renewable energy capacity is evident, as current targets necessitate significant increases to adequately mitigate carbon emissions.

However, delays in the construction and approval processes for new renewable energy initiatives are common, with reports from the International Energy Agency highlighting that extended timelines can obstruct timely integration into national grids.

Beyond concerns regarding competition for electricity resources, AI appears poised to play a critical role in improving energy efficiency across various sectors.

AI tools have been shown to drastically enhance the modeling of optimal wind turbine placements, achieving reductions in site assessment times by factors as high as 4,000.

Efforts in data centers have also shown promise; reports suggest that advancements in AI could lead companies like Google to achieve reductions in cooling energy needs of up to 40%.

Furthermore, AI's potential contributions to battery technology, pivotal for the green transition's success, are significant.

AI can assist in discovering innovative materials for battery production, optimizing maintenance protocols for longer battery life, and providing real-time operational risk assessments.

Despite the promising intersections of AI and green technology, both transitions are confronted with considerable investment challenges.

Reports indicate the European Union will require additional capital ranging from 2.7% to 3.7% of its GDP yearly until 2030 to achieve its green objectives.

Concurrently, an investment gap of approximately 5 to 10 billion euros annually in AI technology has been identified, with stakeholders citing inadequate funding as a major barrier to innovation.

Additionally, examinations of governance frameworks have emphasized the need for robust institutional arrangements to support the adoption of innovative technologies.

Issues such as a shortage of skilled labor, market inefficiencies, and difficulties in labor reallocations across sectors compound these transitions.

The necessity for cohesive policies at both national and EU levels has been underscored as critical to leverage potential synergies between the digital and green transitions, addressing these interconnected challenges is crucial for Europe to maximize the benefits associated with both AI and sustainable practices.