Adoption Telemetry: Measuring Enterprise AI Adoption from Production Signals

Abstract

We introduce adoption telemetry: a method for measuring enterprise AI adoption by computing change-management stage-progression directly from production usage signals. We contribute (1) a framework unifying pre-deployment evaluation gates, production telemetry, and change-management staging into one instrumented system; (2) NANTE, a concrete five-stage operationalization with defined, falsifiable telemetry thresholds; and (3) an open-source reference implementation that we show correctly distinguishes a healthy cohort from five characteristic adoption-failure modes on synthetic populations. We are explicit that the thresholds are proposed constructs requiring empirical validation against real outcomes — a research agenda we outline — not a calibrated model.