AI readiness is a data problem before it is a model problem. Organisations that invest in data engineering — including pipeline architecture, data quality frameworks, and AI-ready data infrastructure — achieve AI deployment timelines up to 60% faster and significantly higher model accuracy than those who treat data as an afterthought.