Data Quality

Enterprise AI programs consistently follow a pattern that frustrates leadership and burns budget. A model performs impressively during development. Benchmarks are strong. Stakeholders approve production rollout. Within weeks of deployment, accuracy drops, business users raise concerns, and the data science team begins the slow process of figuring out why. The model has not changed. The […]