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Inference for GPT-3.5-class performance fell more than 280-fold in two years, so owning your own AI stack now pays off for some companies and wastes capital for others. Twelve questions score which is true for yours and hand you a one-pager for your board.
For a company, sovereign AI means controlling your own models, data, and inference instead of renting everything through vendor APIs. The case rests on four things: how sensitive your data is, your spend at your volume, whether your team can run the stack, and whether owning it creates an advantage rivals cannot copy. Both directions cost money. A company that over-builds pays for hardware it cannot keep busy; one that under-builds pushes confidential data through tools it does not control, and IBM found breaches involving unsanctioned AI cost US$670,000 more than average.
Sources: Stanford HAI AI Index 2025 (inference for GPT-3.5-class output fell over 280-fold in two years); Epoch AI cost research on training and serving large models; IBM Cost of a Data Breach 2025 (shadow-AI breaches cost US$670,000 above average; 97% of AI-related breaches lacked proper access controls).
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