Why AI demands a new kind of infrastructure — and how to build it

Traditional data centers were built for predictable workloads. Then artificial intelligence (AI) happened.

A single AI rack now demands 250 kilowatts (kW) of power compared to the 15 kilowatts that traditional servers require. That’s like trying to power an entire city block through a household electrical outlet.

Data centers consumed 4.4% of U.S. electricity in 2023. That figure is projected to reach 12% by 2028 as AI workloads multiply. Tech giants are pouring over $350 billion into AI-ready facilities while legacy systems buckle under the new demands.

Software-defined data centers offer a path forward, but only for organizations ready to abandon their attachment to outdated infrastructure approaches.

Why legacy infrastructure can’t handle AI demands

AI places a technical strain on infrastructure, and as these workloads grow, their energy demands ripple through budgets and drive up costs across the board.

The power crisis is already hitting budgets. PJM capacity prices will have jumped from $28.92 per megawatt(MW)-day in 2024 to $329.17 per MW-day in 2026, driven largely by data center demand. In Virginia, for instance, residential customers could see bills rise $14-37 monthly by 2040 due to generation costs driven by data center expansion.

Legacy data centers also cannot support edge computing requirements. AI inference often needs to happen closer to where data originates, requiring distributed infrastructure that traditional centralized architectures simply cannot provide.

Software-defined data centers solve these problems by using software to manage configuration and dynamically shape infrastructure to match demand. This approach provides enhanced security and increased agility.

Building AI-ready infrastructure, step-by-step

Creating software-defined infrastructure requires addressing current needs while planning for future growth.

Plan for power and cooling first

…because advanced systems support power densities exceeding 150 kW per rack. Sustainability compliance adds complexity. Europe requires data centers to operate using 100% renewable energy by 2030 under climate regulations. Power planning must now incorporate renewable energy sourcing and carbon footprint management.

Next, build your software foundation

Choose management overlays based on your infrastructure requirements. Today, most data center switching vendors have aligned around VxLAN Fabric (also known as EVPN-VxLAN) as the primary architecture for modern data centers. This design enables scalable, resilient Layer 2 and Layer 3 connectivity across distributed environments — a critical requirement for AI workloads. The result is a flexible underlay that supports dynamic policy management, microsegmentation, and the high east-west traffic volumes AI demands.

Select orchestration platforms that coordinate the entire stack automatically

The selection of automation tools — such as Ansible, Terraform, and other infrastructure-as-code solutions — plays a critical role in streamlining provisioning, policy enforcement, and lifecycle management. Modern platforms include AI-powered capabilities that can predict failures and trigger self-healing policies without human intervention.

Design for shared economics and edge integration

The multi-tenant data center market grew from $39.86 billion in 2023 to a projected $112.38 billion by 2032 as organizations realized they cannot afford dedicated AI infrastructure. Multi-tenant environments enable cost sharing for expensive AI hardware while maintaining security through logical separation.

Finally, plan for rapid scaling

AI demands fluctuate dramatically between training phases and inference workloads. Your software-defined infrastructure must accommodate these variations without manual reconfiguration.

Turn complexity into competitive advantage

Building AI-ready software-defined infrastructure requires expertise that most organizations lack. Power system design for AI workloads, cooling architecture, multi-tenant security frameworks, and orchestration platform selection demand specialized knowledge across multiple technical domains.

That’s where SHI comes in.

We eliminate this complexity through end-to-end infrastructure transformation expertise. We assess your current environment, design power and cooling upgrades, and architect software-defined solutions that support your AI requirements while maintaining security and compliance.

Our services extend beyond infrastructure. We help organizations navigate the entire AI journey — from early exploration and prototyping to full-scale deployment. Through our AI & Cyber Labs, customers can validate use cases, test workflows, and de-risk investments in a safe, expert-led environment.

Our Advanced AI Demo Lab gives teams hands-on access to use cases like code generation, intelligent automation, anomaly detection, vision AI, and conversational interfaces, enabling you to identify the right mix of AI solutions before making major investments.

Our engineers can implement monitoring systems, establish governance frameworks, and optimize performance for AI workloads. This includes selecting orchestration tools, designing multi-tenant architectures that reduce costs while improving security, and planning edge computing integration for future growth.

Additionally, we solve the business case challenge. Our financial modeling quantifies total cost of ownership (TCO), including operational savings from automation and resource optimization, while demonstrating how shared infrastructure reduces AI deployment costs.

The new infrastructure reality

AI infrastructure costs make dedicated data centers unaffordable for most organizations. Multi-tenant software-defined infrastructure makes them accessible.

The organizations building AI-ready facilities — or looking at shared colocation AI workload offerings — today will have competitive advantages tomorrow. Those waiting for costs to drop will find themselves priced out of the infrastructure they need.

Ready to access enterprise AI infrastructure without the enterprise budget? Contact SHI to discover how to make your AI needs achievable.