Traditional data centers only stored, retrieved and processed data. In the generative and agentic AI era, these facilities have evolved into AI token factories. With AI inference becoming their primary workload, their primary output is intelligence manufactured in the form of tokens.
This transformation demands a corresponding shift in how the economics of AI infrastructure, including total cost of ownership (TCO), is assessed. Enterprises evaluating AI infrastructure still too often focus on peak chip specifications, compute cost or floating point operations per second for every dollar spent, aka FLOPS per dollar.
The distinction that matters is this:
Compute cost is what enterprises pay for AI infrastructure, whether rented from cloud providers or owned on premises.
FLOPS per dollar is how much raw computing power an enterprise gets for every dollar spent, but raw compute and real-world token output are not the same thing.
