TL;DR

  • Enterprise infrastructure planning has evolved from default public cloud adoption to a workload-driven approach balancing public cloud, dedicated infrastructure, and regional colocation.
  • Specialized Neocloud platforms provide accessible, high-performance GPU compute required for AI training without the capital burden of dedicated hardware.
  • Edge colocation in secondary markets supplies high-density power, cooling, low latency, and geographic diversity to keep distributed systems connected.
  • Combining Neocloud compute, edge facilities, and public cloud creates a unified framework optimized for cost, performance, and long-term scalability.

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Written by iMiller Public Relations on behalf of fifteenFortySeven.

Enterprise IT strategy has shifted from a “cloud-first” mandate toward a “cloud-smart” philosophy. Rather than forcing all applications onto public cloud platforms, organizations evaluate workloads individually based on specific performance demands, operational costs, and governance requirements. Industry research from Gartner underscores that hybrid cloud adoption is accelerating as businesses seek to match each application with its optimal operational environment rather than standardizing on a single deployment model.

The rise of artificial intelligence has intensified these infrastructure demands, as training and deploying AI models requires specialized GPU capacity that is expensive to build in-house. Neocloud platforms have emerged as a purpose-built solution, enabling companies to access compute-heavy capacity without the complexity of managing dedicated AI infrastructure. However, as McKinsey notes, moving AI initiatives from experimentation into day-to-day production requires reliable, low-latency connectivity back to enterprise systems, public cloud services, and end users.

Regional edge colocation bridges these environments by delivering local physical infrastructure, high-density power, cooling, and network interconnection. As highlighted by JLL, secondary markets continue to attract infrastructure investment due to geographic diversity, capacity expansion, and disaster recovery benefits. By integrating Neocloud platforms with regional colocation, organizations establish an interconnected hybrid architecture where AI model training, sensitive enterprise data, customer-facing applications, and public cloud services seamlessly interoperate.

This content originally appeared on the fifteenFortySeven website and has been adapted for syndication on Data Center POST. Read the complete blog here.