Scaling Agentic AI: How llm-d Enables Infrastructure Sovereignty
Red Hat, Wednesday, August 19th, 2026
Red Hat argues open models alone do not deliver sovereignty when AI strategy still depends on constrained accelerator supply.
Red Hat argues AI is entering an era of large-scale, distributed, agentic systems in which applications coordinate multiple models, tools and services across millions of requests.
Infrastructure costs keep climbing while access to AI hardware remains constrained by supply chains, vendor roadmaps and rapidly evolving accelerator technologies. This creates a new kind of dependency: organizations have adopted open models and kept ownership of their data, yet their AI strategy still hinges on hardware they do not control.
Red Hat positions llm-d as the layer that restores independence at the infrastructure level. The argument extends the sovereignty debate from data and models to serving capacity.