The European data center market, a bustling sector valued at US$14.2 billion by 2028, is on the cusp of a significant transformation. In the heart of this change is the burgeoning influence of Artificial Intelligence (AI). The integration of AI into data center infrastructures is not just a trend, but a necessity in the face of rising demand for data processing and storage.
In Europe, the market has evolved rapidly over the past decades, with the rise of cloud computing, video streaming, and 5G networks more recently driving a surge in demand for data processing and storage. However, the traditional data center infrastructure is no longer sufficient to support the next level of digital transformation that AI promises. JSA Media Consultant João Marques Lima explains in this feature article.
AI brings far-reaching implications for data center development and demand. It is redefining traditional data center networks, altering the functionality of these facilities, and shifting the geographical distribution of data center clusters.
In the European Union (EU), the AI Act (AIA) is shaping the regulatory landscape for AI. This comprehensive regulatory scheme, although primarily designed for the EU, has a global impact. It is particularly influential in sectors like data center operation, where AI systems are increasingly integrated.
The AIA’s extraterritorial impact varies across sectors and applications. Its provisions affect AI systems in regulated products around the world, demonstrating a clear “Brussels Effect”. However, the EU’s global influence over online platforms may not be as substantial as policymakers suggest. Therefore, a more collaborative approach with other governments on AI governance would be beneficial.
That is especially important as, according to IDC, worldwide revenue for AI is projected to surpass US$300 billion by 2026, representing a 27% compound annual growth rate. This growth rate is more than four times the growth rate of overall IT spending over the same timeframe, indicating the significant economic impact of AI.
In the European data center market, the rise of AI is causing a paradigm shift. AI-driven data centers offer numerous benefits, such as the ability to slash downtime, enhance overall system reliability, and translate into massive cost savings for organizations. The integration of AI into data center infrastructure also brings about a high cost in terms of processing performance and power consumption.
Implementing an AI and Machine Learning (ML)-driven layer within traditional data center architectures creates autonomous data centers that can optimize and perform generic data engineering tasks without human intervention.
AI-driven data centers improve event detection and prediction abilities, offering fast failure detection and triggering self-healing mechanisms. AI also provides a clear picture of app resourcing levels, allowing for nimble scaling to meet demand in real-time.
AI, Data Center Architecture and Power
The need for new architectural designs is evident, considering the changing landscape of platforms, equipment design, topologies, power density requirements, and cooling demands.
Edge computing, which processes data closer to the source, is emerging as one of the most promising technologies for developing AI-driven data centers. This technology reduces latency and improves overall performance. When combined with AI, it offers the potential to achieve real-time analysis and decision-making capabilities, making data centers capable of handling mission-critical applications in the future.
On the power front, AI applications consume significantly more versus traditional set ups. For example, high-performance processors required for AI need more power than traditional data center processors. Additionally, AI applications necessitate modifications for cooling technology to reduce downtime.
This will lead to a spending rush to replace and install newer hardware. Tirias Research forecasts that generative AI data center server infrastructure plus operating costs will exceed US$76 billion by 2028. This cost estimation takes into account the current course of generative AI, incorporating an aggressive 4X improvement in hardware compute performance. However, this gain is overrun by a 50X increase in processing workloads, even with a rapid rate of innovation around inference algorithms and their efficiency.
As AI demands more power, data center operators must meet sustainability requirements and reduce greenhouse emissions. According to a study by JLL, the sector now accounts for up to 4% of greenhouse gas emissions globally. The market’s growth will be directly influenced by environmental, social and governance (ESG) requirements.
Modern data centers are addressing these problems by deploying, you guessed it, AI. Coupled with automation, IoT, and ML, AI is helping many operators design and build lean and smart data centers. AI and robotics solutions not only help improve energy efficiency and reduce carbon emissions, but also automate routine activities, reducing workforce requirements.
As organizations across Europe begin to realize the potential of AI in data centers, we will see better energy management all across. For instance, data center operators are using AI to improve energy efficiency by managing Power Usage Effectiveness (PUE) proactively, monitoring a facility’s hardware to extend its usable life, planning a data center’s physical space, and also monitoring temperature and humidity constraints.
Elsewhere in the AI playing field, customers can deploy AI software from data centers for service chatbots, marketing analytics, data visualization, lead generation for business development, self-driving cars, and insurance and fraud detection.
The growing integration of AI in data centers also affects the job market in this sector. While AI reduces the need for certain manual tasks, it also opens up new opportunities for skilled workers. As data centers become more autonomous, the demand for AI and ML experts increases.
The transformation carried by AI on European data centers is and will be profound, influencing the regulatory landscape, economic implications, and the operational aspects of data centers. As AI continues to evolve, so will the hosting landscape, embracing new technologies and strategies to meet the growing demand for data processing and storage, while addressing the environmental challenges that this growth entails.