Where is the line between heavy API usage and systematic model extraction?

As API-based foundation models scale, I’ve been thinking about the boundary between normal high-volume usage (benchmarks, evaluation runs, synthetic data generation) and structured querying designed to approximate or distill capabilities. At what point does usage meaningfully become “model extraction,” and is that even a technically enforceable distinction? It seems like: * Call count alone isn’t meaningful * Token volume matters * Structured prompt variation might matter * Intent is almost impossible to prove I’m curious how people here think about this from both a technical and governance perspective.