Will the median trailing gross margin of US-listed AI-native application software companies reporting AI inference as cost of revenue be at least 70% in their fiscal 2027 filings?

The case against it

Introduction of real inference costs that scale with customer usage instead of marginal cost approaching zero, so traditional J-curve where customer lifetime value rises with retention no longer holds; retained customers become more expensive to serve, compressing margins. Enterprise AI adoption whose per-seat compute and inference spend rises faster than the wage bill it displaces, so budgets exhausted early, licenses cancelled, and margin drag disclosed on earnings calls. It would show first if median gross margin for the cohort stays below 70% or declines year over year in fiscal 2027.

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