Rethinking Data Center Design and Implementation for the AI Era - June 23, 2025
June 23rd, 2025 By Staff Reports
As digital demands intensify across every sector of the economy, data centers are emerging as both vital infrastructure and operational bottlenecks. The exponential growth of AI, cloud services, and high-performance computing has placed new strains on power availability, cooling capacity, and skilled labor—forcing a rethinking of what it means to be “future-ready.”
In a recent BizTechReports executive vidcast, Vigilent Founder, President and CTO Cliff Federspiel discussed the strategic evolution of data center management in this high-pressure environment.
NOTE: His insights have been edited and organized into four sections: strategic imperatives, operational consequences, financial implications, and technological deployment to help enterprise leaders make informed decisions about infrastructure planning and optimization.
Here is what he had to say:
STRATEGIC IMPERATIVES
BTR: What are the primary forces reshaping the strategic role of data centers today?
Federspiel: Growth is happening on all fronts—more data centers, more power consumption, more performance density. We’re seeing 1.5x year-over-year power growth in some regions. AI workloads, especially training, have redefined what data centers need to deliver. Traditional architectures can’t meet these demands without major changes.
But here’s the inflection point: data centers used to be seen as facilities. Now, they’re critical components of enterprise value chains. That means the strategic focus has shifted. Location decisions are now driven by power availability and latency requirements, not just cost. Older facilities are being retrofitted. And microgrids, hydrogen, and alternative energy sources are entering the mix—especially where grid connectivity is a bottleneck.
BTR: What should enterprise decision-makers prioritize when selecting or partnering with data center providers?
Federspiel: Think like a hyperscaler. That means demanding visibility, modularity, and scalability. The best operators today design with flexibility in mind. They don’t assume workloads will stay the same or that cooling needs won’t evolve.
Enterprises should look for three things: 1) scalable infrastructure that can handle increased density; 2) a sustainability roadmap—especially around water use and carbon; and 3) operational transparency, including real-time telemetry and SLA enforcement. These are no longer nice-to-haves—they’re table stakes for future-proofing.
OPERATIONAL CONSEQUENCES
BTR: What are the operational challenges data centers face as workloads become more intense and customer demands more diverse?
Federspiel: Density and complexity are the two big drivers. As rack power increases—from 5–10 kW a few years ago to 40 kW and beyond today—cooling becomes a much more complicated problem. We’re seeing increased use of containment, adoption of rear-door heat exchangers, and innovation in direct-to-chip liquid cooling.
The challenge is that these new technologies require operators to evolve. They need engineered flexibility. And they need automation. At the same time, staffing shortages are becoming critical. The average age of data center professionals is over 45, and there’s a limited pipeline of skilled talent.
To address that, operators are turning to intelligent software to automate monitoring, cooling optimization, and asset management. Systems like Vigilent's enable them to do more with less—running larger facilities without linear increases in staff.
BTR: How is the edge influencing operational models?
Federspiel: Edge deployments are growing as more applications—like gaming, VR, and autonomous vehicles—require ultra-low latency. That’s driving investment in smaller, distributed data centers closer to end users. Old telco sites are being reactivated and modernized.
But operationally, these edge sites must be managed with the same rigor as large hubs. That requires integrated software systems, consistent performance monitoring, and remote automation. The ability to operate uniformly across centralized and distributed assets is becoming essential.
FINANCIAL IMPLICATIONS
BTR: What economic dynamics are emerging as the data center market grows more competitive and resource-constrained?
Federspiel: We’re in a paradoxical moment: demand is skyrocketing, but resources are constrained. Power access is limited. Water use is under scrutiny. Labor is expensive and scarce. So, while demand is high, margins can shrink quickly if operators don’t manage resources efficiently.
That’s why data centers that invest in operational intelligence—cooling optimization, predictive maintenance, automated monitoring—are better positioned financially. They reduce waste, extend equipment life, and improve SLA compliance. These efficiencies translate directly into financial resilience.
Colocation is growing fast, especially in the mid-market, but enterprises need to be smart consumers. Look for providers that already serve hyperscalers. Their infrastructure will be more mature, and the transparency required by hyperscalers will benefit everyone.
BTR: How should enterprises evaluate ROI when upgrading or selecting data center infrastructure?
Federspiel: Think beyond cost per kilowatt. Consider performance per kilowatt-hour, equipment longevity, and risk mitigation. How quickly can you detect a thermal anomaly? How easily can you add new capacity? What’s your exposure if you lose a key operator?
Financially speaking, automation and intelligence reduce operational risk and improve predictability. That matters more than ever when workloads are volatile and infrastructure needs to scale rapidly
TECHNOLOGICAL DEPLOYMENT
BTR: What technologies are redefining best practices in infrastructure management?
Federspiel: AI-driven control systems are now essential. They dynamically manage cooling based on real-time thermal conditions, not just static thresholds. This improves efficiency and reduces manual intervention.
Liquid cooling is the next major shift. We’re seeing a market convergence around direct-to-chip systems, especially for AI and high-performance workloads. Immersion has its advocates, but in practice, most new deployments are leaning toward chip-level cooling due to flexibility and maintainability.
Also critical is telemetry. Hyperscalers demand it—and enterprises should too. Operators must be able to expose power, cooling, and environmental metrics in real time. That allows customers to enforce SLAs, identify inefficiencies, and plan growth intelligently.
BTR: How does software-driven manageability shape competitive advantage for data center operators?
Federspiel: Software is the multiplier. With skilled labor in short supply, intelligent systems fill the gap. Whether it’s DCIM, asset management, or thermal optimization, the ability to automate and visualize performance is becoming a competitive differentiator.
The most advanced customers are already asking for this. They're demanding not just uptime, but insight. Operators that can deliver both will earn trust—and market share.
Closing Thoughts:
As AI, edge computing, and digital transformation continue to reshape enterprise infrastructure, data centers must evolve in kind. Scalability, sustainability, and manageability are no longer optional—they are core criteria for long-term success. Enterprise leaders evaluating data center partnerships must think like hyperscalers, insist on transparency, and invest in intelligent systems that turn operational complexity into strategic advantage.
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