How AI 2025 data center trends impact edge computing

In addition to Vertiv’s AI trend predictions, another influence on the edge is an industry shift to cloud repatriation, which puts additional emphasis on edge sites. With enterprises reconsidering their reliance on the public cloud, some workloads are returning to on-premises and remote edge infrastructure due to rising costs, regulatory pressures, and performance needs. This movement highlights the increasing importance of the edge in complementing hybrid IT strategies, including AI applications and the high power demands of AI inferencing applications. importance of the edge in complementing hybrid IT strategies, including AI applications and the high power demands of AI inferencing applications.

Power and cooling infrastructure innovates to keep pace with computing densification

The densification of computing workloads is driving innovation in power and cooling solutions. AI applications demand increasingly efficient systems to manage the power requirements and thermal output of high-performance computing. Inferencing at the edge provides critical benefits such as reduced latency and enhanced security, making it an essential strategy for managing AI workloads efficiently in edge deployments.

Edge deployments often occur in less traditional locations, requiring robust equipment capable of operating in diverse conditions. Modular cooling systems, whether air or liquid cooling, are evolving to enable businesses to scale edge deployments without compromising energy efficiency or reliability.

Prepare for future-friendly edge applications with cutting-edge cooling technologies and energy-efficient uninterruptible power supply system solutions. 

Prioritize energy availability challenges

Energy availability is becoming a major concern as the demand for compute capacity grows and power densities increase. At the edge, this challenge is particularly pronounced due to distributed locations with varying access to power. AI applications further complicate this issue, as they require consistent and scalable energy sources to maintain operations.

Companies are adopting renewable energy integrations, high-efficiency power systems, and alternative energy sources to address this gap. Additionally, energy management strategies are evolving to optimize consumption, reduce costs, and improve sustainability. For edge deployments, local energy solutions like microgrids and battery storage systems are gaining traction, ensuring uninterrupted operations even in remote or underserved areas. For long-term power security, evaluating alternative energy solutions and energy management tools to address availability challenges and resilience in edge environments.

Industry players collaborate to drive AI factory development

The development of AI-driven infrastructure, or “AI Factories,” is a collaborative effort requiring input from various industry players. Chip manufacturers, critical digital infrastructure providers, utilities, and end-users are working together to align on reference designs, deployment strategies, and timelines for future-friendly AI deployments. These partnerships are crucial in developing edge infrastructure that is equipped to meet the demands of future AI workloads.

Collaboration is particularly important for creating scalable and efficient solutions. For example, chip manufacturers like NVIDIA work with industry power and cooling infrastructure providers to integrate seamlessly with their chips for faster deployment and more efficient operation. Customers work with industry players to develop solutions for specific needs – like transitioning to mixed traditional and AI loads. Meanwhile, partnerships with utilities are helping to address energy challenges through innovative grid solutions.

Businesses should consider working directly with trusted industry stakeholders for options to address unique challenges, and watch for collaborations and reference designs to strategize their edge deployments effectively.

Government and industry regulators tackle AI applications and energy use

As AI adoption continues to expand, governments and industry regulators are stepping in to address its implications, including energy use, carbon emissions, and intense scrutiny of how AI can be applied. 

Sovereign AI, including regulatory frameworks like the EU’s AI Act are shaping how and where AI can be deployed, with significant impacts on edge computing. At the edge, compliance with these regulations becomes even more complex, with issues impacting data processing that crosses regional boundaries. Businesses must navigate these regulations while ensuring their deployments remain efficient and scalable.

To ensure compliance, monitor regulatory changes closely, and implement scalable and energy-efficient edge solutions to comply with evolving guidelines.

Looking ahead: shaping the future of data centers

AI adoption is nascent and continuously evolving in general, and this is especially true at the edge. Predictions provide a direction, but not a crystal ball. As power-intensive inferencing applications are deployed at the edge, we are all waiting to see how this adoption will impact space considerations and power demands, and how all will be impacted by energy and usage regulations. Deploying scalable and energy-efficient power and cooling systems and environmentally rugged enclosures are a good strategy that should serve edge operators well as their AI strategies mature.

About the author

Alex Johnson is a seasoned sales leader with extensive experience in channel partnerships, distribution strategy, and IT infrastructure solutions. With over a decade in the industry, he has a proven track record of driving growth, cultivating key relationships, and developing go-to-market strategies for high-performance data center technologies. Since joining Vertiv in 2018, Alex has held multiple channel leadership roles across Partner, Distribution, and Field sales. In his current role as Senior Director, North America Partner Sales, he leads strategic initiatives to expand Vertiv’s channel ecosystem and support the evolving needs of data centers and IT infrastructure providers. His expertise in power and cooling solutions, partner enablement, and sales operations plays a critical role in driving Vertiv’s channel growth across North America.

Article Topics

AI  |  AI factory  |  AI/ML  |  data center  |  edge computing  |  edge data center  |  Vertiv