Data Sovereignty: Who Owns Your Data When AI Runs Your Workflows

Alex Karp went on CNBC and said out loud what most operators already suspected. The closed model companies are not going to stay in the intelligence business. Intelligence is becoming a commodity, the margin sits in the workflow, and the workflow is yours.

This is a working session on what that means for a company that is not in the S&P 500.

We cover why the supply of public training data has effectively run out and private data is the only path left, what the Anthropic and Figma sequence looks like from the outside, why a middle-market company has no realistic legal remedy against a trillion dollar counterparty, and why we think today is the highest market share OpenAI and Anthropic will ever hold even as their revenue keeps growing.

Then the practical half. Three routes to running open source models against your own proprietary data: hosted inference, your existing cloud, or local hardware. All three keep the data inside infrastructure you already control, under terms you set rather than terms you accepted. That is a decision a CTO can make this quarter.

The argument underneath all of it is short. "We use AI" is not an asset. "We own the data, the process, and the model that runs on it" is.

Score your own exposure with the Data Sovereignty Diagnostic, a five-part self-assessment across data ownership, egress and portability, model and IP rights, process ownership, and vendor concentration. It ships with the August paper. Link on the first line.

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