Owning your LLM and ML model infrastructure is often framed as a cost decision. But what happens when the models running on that infrastructure are part of your company’s core intellectual property? A session at RenderATL (Render Atlanta) about Physical AI got me thinking about where the real risk sits as AI moves from demos into production. When LLM and ML models depends on infrastructure owned by someone else, your data, model outputs, and API traffic cross a boundary you do not fully control. This is why securing these boundary is everything!
Models are increasingly connected to private data, internal tools, and business processes that companies would never willingly hand to a competitor. We have already seen how valuable behavioral and product data can become. 3rd party model providers adds another layer to that problem because the inputs and outputs can reveal how valuable systems work. The economics of GPUs still matter, especially for smaller teams, but infrastructure ownership is becoming a conversation about privacy, intellectual property, and control too.
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