Exyte, a global specialist in the design, engineering, and construction of advanced technology facilities, has been awarded three significant data center projects in the Greater Frankfurt area. Secured from leading hyperscale operators and major technology firms, the contracts have a combined value of nearly €750 million, recorded as order intake for 2026. The projects are also expected to create approximately 400 jobs across Germany.

“These new awards highlight the growing importance of the data center sector within Exyte’s portfolio and reinforce its position as a major engine of growth,” said Mark Garvey, Chief Commercial Officer at Exyte. “With demand for artificial intelligence and cloud-based services expanding rapidly worldwide, reliable and scalable digital infrastructure is becoming essential for maintaining our clients’ competitive advantage.”

The latest wins further strengthen Exyte’s reputation as a trusted partner for global technology companies and build upon its extensive experience delivering data center developments in the Frankfurt market.

The three contracts encompass both the construction of new facilities and the expansion of existing sites, with all projects being executed simultaneously. Some of the work will be carried out within operational data centers, requiring meticulous planning and coordination to maintain uninterrupted service while increasing capacity. Together, the facilities will provide approximately 80 megawatts of IT load capacity and are scheduled for completion by 2028. Rapid and dependable delivery remains a critical priority as customers seek to expand infrastructure in response to rising demand.

Workforce Expansion to Support Delivery
To meet project requirements, Exyte plans to add around 400 positions in Germany. Approximately 150 roles will be filled through the redeployment of experienced personnel from other projects within the company, while the remaining 250 positions will be recruited externally.

Hiring efforts will span a variety of disciplines, including engineering, technical services, project controls, construction management, and commissioning. Employees will work within international, multidisciplinary teams on large-scale infrastructure developments, contributing to technologies that support the future growth of AI and digital services.

Advancing Digital Infrastructure for an AI-Driven Future
The Frankfurt projects are part of a wider surge in investment across Europe’s data center sector. Growing AI adoption, increased reliance on cloud computing, and the need for secure and resilient digital ecosystems are driving demand for large, high-density facilities.

“Data centers are now a cornerstone of modern economic infrastructure,” said Jürgen Raschendorfer, Chief Operating Officer for Exyte’s Continental Europe region. “These projects expand our established presence in Frankfurt and help clients increase capacity, improve resilience, and deliver next-generation digital services in one of Europe’s most important data center hubs.”

Focus on Delivery Excellence
Exyte attributes its success to a delivery model that combines advanced engineering expertise with highly standardized and industrialized construction methods.

“What sets Exyte apart is our ability to execute large-scale data center programs with confidence in cost, schedule, and quality outcomes,” said Damian Farr, President of Exyte’s Global Business Unit Data Centers. “This capability is especially important in live operational environments, where careful coordination and integrated execution are essential to avoid disruptions.”

Modern data center designs are also evolving to support higher power densities and sophisticated cooling technologies needed for AI-driven workloads. Exyte leverages offsite manufacturing and prefabrication techniques to accelerate project delivery, improve quality standards, and reduce construction risks.

To meet increasing energy requirements, the company incorporates flexible power infrastructure and resilient backup systems that enhance operational reliability. Digitalized delivery and commissioning processes provide greater predictability across project timelines, costs, and quality metrics. In addition, Exyte’s established supply chain network and category management strategy help secure access to critical equipment and specialist partners despite ongoing market constraints.

These capabilities enable customers to bring facilities online more quickly, achieve greater operational reliability, and expand digital infrastructure with confidence.
 

Artificial intelligence (AI) and machine learning (ML) are rapidly reshaping industries and daily life, yet this progress comes with a rising environmental cost. Large-scale data centers require immense amounts of electricity and water, and the production of advanced hardware demands significant natural resources.

To counter these impacts, materials scientists are developing new solutions that enhance durability, improve energy efficiency and increase the resilience of the infrastructure that supports AI. Dow, for instance, uses advanced materials science to create technologies that improve thermal management in data centers. These solutions allow cooling systems to run more efficiently than conventional air-cooled systems, reducing energy use and helping cut greenhouse gas (GHG) emissions.

These advancements demonstrate how focused innovation can mitigate AI’s environmental footprint and encourage a more responsible, sustainable digital landscape.
 
What Is the AI Ecosystem?
The AI ecosystem refers to the expanding, interconnected system of technologies, data centers, hardware, organizations, and operational processes that enable the development, deployment and use of artificial intelligence.
 
Key Points

 
Environmental Impacts of AI
AI’s environmental effects span the entire lifecycle of its systems—from production to operation to disposal. Data centers, which supply the computing power for AI, consume enormous amounts of electricity. By 2026, these facilities may use around 1,050 terawatt-hours of power—enough to rank them as the world’s fifth-largest energy consumer if they were a country. When this energy comes from fossil fuels, it significantly increases GHG emissions.

Water consumption is another major concern. Cooling technologies used in data centers and power plants require vast amounts of water, with global usage projected to reach up to 6.6 billion cubic meters annually by 2027. The rapid development cycle of AI hardware also accelerates the generation of electronic waste; by 2030, as much as 5 million tons of e-waste could result from upgrading devices and components to support more advanced AI models.
Addressing these impacts is crucial to ensuring AI’s growth aligns with global sustainability goals.
 
Key Areas of Environmental Impact
Energy Use
Training and operating modern AI systems demands extensive electricity. Cooling alone can represent up to 40% of a data center’s consumption in dense computing environments. Solutions include developing more efficient algorithms, improving hardware, and relying on renewable or lower-carbon energy sources.

Water Use
Water is heavily used in cooling processes and in power generation that supports AI infrastructure. As AI adoption accelerates, reducing water usage and finding water-efficient cooling technologies will be increasingly important.

Land Use
Expanding data center infrastructure often requires large areas of land, potentially disrupting ecosystems and increasing resource extraction in previously undeveloped zones.

Climate Impact
AI can support climate resilience by helping optimize resource use and forecast environmental conditions. However, without sustainable development strategies, the energy demands of AI systems may contribute to global emissions.
 
Advancing Sustainable AI
As the demand for AI grows, so does the need to make its development more environmentally responsible. High-performance computing strains power grids and increases emissions unless efficient cooling, responsible sourcing, and circular design principles are used.

Manufacturing components like processors and semiconductors often involves intensive mining and large volumes of water and energy. Taking a full lifecycle approach—from material sourcing to end-of-life disposal—is essential to minimizing environmental harm.

According to Brendy Lange, President of Performance Materials & Coatings, customers increasingly recognize that long-term sustainability requires innovation at the materials level, motivating deeper collaboration to design solutions that can withstand the demands of advanced technologies, including AI.
 
Material Innovations Driving a Sustainable AI Future
Advanced materials are essential to supporting next-generation AI systems and communication networks.

Consumer Devices
AI-enabled devices—from smartphones to wearables—depend on materials designed to manage heat, enhance durability and reduce waste. Dow’s innovations help improve thermal performance and extend device lifespan. Reusable or recyclable materials, such as DOWSIL™ TC-3015 Re-workable Thermal Gel, support circularity in consumer electronics.

Cloud and Data Centers
Overheating reduces data center efficiency and accelerates equipment failure. Dow provides heat transfer fluids, thermal interface materials and silicone encapsulants that help manage heat effectively. These solutions support liquid cooling, immersion cooling and long-lasting thermal performance, enabling operators to reduce energy consumption and extend hardware life.

Telecom Infrastructure
Telecom systems must withstand extreme environmental conditions. Silicone-based adhesives, sealants, and protective coatings protect components from moisture, dust, and thermal stress. Dow also offers cable innovations—such as AXELERON™ and ENDURANCE™ compounds—that improve power delivery and data transmission while supporting circularity through materials like REVOLOOP™ recycled resins.
 
Additional Sustainable AI Strategies
Organizations committed to sustainability are implementing:

These practices create a foundation for an ethical and resilient AI-driven future.
 
Meeting AI’s Energy Demand With Advanced Nuclear Power
Major technology companies are beginning to invest in small modular nuclear reactors to supply clean, reliable energy for large data operations. These reactors offer near-zero emissions and fill energy gaps where renewables may not be sufficient. Dow is similarly exploring advanced nuclear technology with X-energy to reduce emissions at its Seadrift Operations site on the U.S. Gulf Coast.
 
Building a Sustainable AI Future
Sustainable development must be embedded throughout the AI ecosystem. By adopting clean energy sources, using efficient materials and designing systems with circular principles in mind, organizations can reduce AI’s environmental footprint while maintaining high performance.

As AI becomes integral to everything from personal electronics to communications networks and cloud computing, sustainable design will be essential to balancing technological advancement with planetary well-being.

These collective efforts highlight the critical role sustainability plays in shaping AI’s future—creating solutions that support both the environment and the accelerating digital world.