Enterprise IT infrastructure isn’t built for AI inference
As global AI investment continues to climb — it surpassed $300 billion in 2025, according to IDC — enterprise IT remains primarily focused on supporting the development of training models, with architecture such as large GPU clusters and high-density compute taking center stage.
But now AI inference is becoming the dominant workload, and the architecture that supports models in production, at scale, and to real users and systems has quickly become the future of AI.
The demand for AI inference is there — according to Deloitte, inference already accounts for roughly two-thirds of compute, while McKinsey projects that it will represent between 30% and 40% of total data center demand by 2030 — however, the dedicated infrastructure is not.
CEO of Megaport.
Inference is more than a scaled-down training environment
What training and inference require from an IT point of view are very nearly polar opposites. Enterprises have facilitated AI...
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