Tune source freshness, supplier coverage and data-quality gates, then pick how far to automate. Automate on poor data and the model amplifies your errors - readiness is what makes automation safe. Press Run to start.
AI amplifies whatever data it is fed. With poor freshness, coverage or quality, higher automation multiplies operational risk instead of value - readiness is a precondition, not an afterthought.
Each round your data-quality dimensions combine into a composite score; the chosen AI mode sets the automation level. Benefit rises with automation, but risk rises with automation × (1 − data quality), and strict gates cost throughput.
Raise data quality before escalating automation. Move to Autonomous only once freshness, coverage and gates are strong, and gate only as tightly as quality actually requires.
