Every metadata professional has built their own audit framework. Every audit measures different things. Two consultants can look at the same dataset and come back with two completely different answers. That is not a standard. That is a consulting opinion.
This session introduces MQS (Metadata Quality Score), a fixed, published scoring model for structural metadata governance. We will walk through the nine signals it measures across two dimensions (Control and Intentionality), what it deliberately does not measure, and how an AI Readiness overlay reweights those same signals to answer whether metadata is structurally ready for machine consumption.
The session will cover the impact on practitioners, service providers, DAM/PIM/MAM platforms, and brands, and will open the question of what it will take for the broader community to align around a shared measurement standard.