When planning for AI, GPUs and compute power often take center stage—but the real cost risks often come later, from the infrastructure decisions that get overlooked early on. Power distribution, cooling, cabling, and rack design may seem like secondary concerns, but skipping over the details can lead to inefficiencies, downtime, and expensive redesigns down the road.
For experienced data center teams, the challenge is building infrastructure that can handle AI’s intensity and unpredictability—without overbuilding or leaving gaps that hurt long-term ROI.
In this post, we’ll highlight five commonly missed infrastructure considerations that can quietly increase costs —and how to avoid them through smarter planning.
Power Blind Spots That Compromise Uptime
AI requires more power. But how much more—and how to plan for it—isn’t always obvious. Bursts, surges, and uneven loads demand more than capacity, they require precise monitoring, deep visibility, and built-in headroom.
Common AI power pitfalls include:
- Assuming one level of monitoring fits every workload: Without outlet-level insight, you risk missing early signs of overload or imbalance. Microbursts and spikes happen without warning.
- Prioritizing upfront cost over long-term reliability: Choosing minimal monitoring to save money can backfire when downtime or hardware failures hit.
- Overlooking physical space for power infrastructure: Cramped cabinets, poor airflow, and design compromises all hurt reliability and scalability.
The Fix: Build in Monitoring, Headroom, and Physical Space from Day One
- Start with the right level of monitoring for your workload:
- Input-level metering shows total draw and helps validate load balancing, giving you a top-level view of how much power is being used overall.
- Branch-level metering catches imbalances or overloads in circuit groups.
- Outlet-level monitoring reveals real-time usage at each outlet, tell you exactly how much capacity you have left before adding a new device.
- Factor in headroom: Too many teams plug into PDUs thinking they have room to grow—only to find out too late that they’ve already hit the limit. The volatility of AI workloads demands more headroom. High-power PDUs with 60A or 100A circuit breakers offer more capacity and margin of safety.
- Plan for physical space: Redundant power may require two, four, or more PDUs per cabinet. Account for this early on in the planning process to avoid conflicts with cabling and airflow paths.
Looking for high-power PDUs? Explore CPI’s for intelligent metering, switching options, and scalable configurations.
Cable Congestion That Strains Performance
In AI environments, cabinets aren’t just full of servers—they’re packed with high-speed cabling, liquid cooling lines, and dense connections. Poor cable management has a direct impact on performance and maintenance.
A few real consequences of congestion include:
- Blocked airflow compromises thermal performance and drives up cooling costs.
- Strained or bent cables can degrade optical performance and cause unpredictable packet loss.
- Tight, messy routing increases the risk of accidental disconnections and slows down routine maintenance.
- Higher mean time to repair (MTTR) due to unlabeled, overcrowded bundles that are hard to trace and manage.
What’s manageable at 10 racks becomes unmanageable at 100 if cable organization isn’t built into the infrastructure from day one.
The Fix: Design for Density and Day-Two Operations
Look for cable management systems that offer:
- Clear, defined pathways that separate power and data cabling
- Bend radius protection to maintain signal integrity, especially for fiber
- Tool-less adjustability for faster MACs (moves, adds, and changes)
- Adequate sizing from the start—account not just for day-one cable fill, but for future growth. Once installed, your options to scale are limited.
For open racks, CPI’s supports high-density environments with snap-in accessories and intuitive routing.
For cabinet-based deployments, explore the , equipped with integrated vertical and horizontal cable management options for organized, scalable deployments.
Hidden Airflow Gaps That Undermine Cooling Efficiency
Most organizations need to deploy AI today—not two years from now in a new liquid-cooled facility. That means making existing air-cooled environments work harder, and smarter.
The key to doing that? Airflow management.
Too often, cooling efficiency is compromised by partial containment, leaky rows, or inconsistent zoning. When cold and hot air mix, even small inefficiencies add up:
- Recirculated exhaust air increases inlet temperatures
- Cooling units become oversized to compensate
- Nodes throttle or fail due to inconsistent intake temps
The Fix: Seal the System. Unlock Thermal Headroom.
Be diligent about sealing all gaps (seen or unseen!). Install and other airflow management accessories early—they may seem minor, but these simple additions can make or break your cooling strategy.
For higher-density environments, passive solutions like CPI’s are especially effective. VED uses the laws of thermodynamics to direct exhaust from the top of the cabinet into the ceiling return plenum—no additional fans required. This helps prevent recirculation, even as densities climb.
For quick deployment of Hot Aisle Containment, CPI’s installs rapidly with preassembled, height-adjustable panels—no fabrication required.
These upgrades improve efficiency and give you thermal flexibility before investing in advanced cooling.
Waiting Too Long to Design for Liquid Cooling
Many teams delay liquid cooling due to concerns about immersion tanks, retrofits, or facility disruption. But there are multiple paths to liquid cooling—and not all of them are drastic.
Two-phase, direct-to-chip cooling stands out as a practical, high-impact solution for AI workloads that can be integrated into existing data center strategies with minimal disruption.
Too often, teams treat liquid cooling as a future problem—until it becomes an urgent one.
The smarter move? Design with a hybrid mindset from the start.
Designing with hybrid cooling readiness from the outset—supporting both air and liquid in a unified infrastructure—gives you the flexibility to scale thermally without committing to a full redesign.
Choosing a cabinet like CPI’s two-phase direct-to-chip cooling, provides a turnkey, scalable solution.
Here’s how it sets you up for long-term success:
- ZetaFrame® Cabinet with ZutaCore® integration offers hybrid support for both air and liquid cooling.
- ZutaCore’s direct-to-chip cooling extracts heat at the source—removing up to 2800W per chip—with your existing infrastructure.
- Waterless Technology Cooling System (TCS) loop minimizes risk of leaks making it safe for enterprise and colocation environments alike.
- Phased adoption allows you to start with air cooling and evolve to liquid cooling as power densities demand—without needing to overhaul your entire layout.
With two-phase liquid cooling, you gain the ability to evolve your strategy over time—on your terms, not in response to a thermal crisis.
Slowing Down Speed of Deployment with Ad Hoc Infrastructure Choices
Power, cooling, cabling, airflow, space—each element adds complexity. Once you introduce liquid cooling, you're layering in more power, more cable management, and less available space. Suddenly, your cabinet must do it all—and do it well.
The common misstep? Piecing together infrastructure from multiple vendors or mismatched components. It slows everything down. Compatibility issues surface. Lead times stretch. Installations get messy.
The Fix: Start with an Integrated Cabinet Platform Built to Scale
The consolidates your critical infrastructure needs into a single, high-performance solution:
- High-Power eConnect® PDUs preinstalled for high-density, redundant power
- Built-in liquid cooling support with ZutaCore® integration
- Integrated cable and airflow management
- Industry-leading load capacity of up to 3,500 lb. (1,587 kg) to support today's heaviest AI and HPC hardware
- Modular, scalable design that speeds up deployment and reduces complexity
Instead of redesigning your setup with every deployment, you build once—and scale confidently.
Get Expert Support for AI Infrastructure Planning
At CPI, we don’t just manufacture AI-ready infrastructure—we help you plan for it.
Our experts are available to understand your goals, challenges, and environment and offer practical guidance through free consultations and field-proven strategies.
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