Info-Tech Blueprint Maps AI Infrastructure to Workloads

Oct 6, 2026
Info-Tech Research Group released a framework that helps enterprises align AI infrastructure with the demands of training, inference, retrieval augmented generation, agents and edge workloads.

Info-Tech Research Group released a blueprint for designing AI infrastructure around workload requirements rather than adding compute capacity by default. The framework covers training, inference, retrieval augmented generation, agentic AI and edge AI workloads.

The blueprint treats compute, memory, storage, networking and physical infrastructure as connected parts of one system. It notes that AI traffic often moves between computing systems, requiring higher bandwidth and lower latency than conventional user facing enterprise traffic.

Its five phases cover assessing demand patterns, matching processors and infrastructure to workloads, identifying constraints, designing balanced architectures and establishing operating strategies for cost and risk. An accompanying assessment workbook helps organizations profile workloads, compare seven reference architecture patterns, shortlist vendors, estimate costs and simulate deployment scenarios.

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