Procter & Gamble's Senior Automation Manager, Adonis Castillo Cordero, shares how his team modernizes legacy data systems and powers AI workloads across a global enterprise using Apache Airflow as the orchestration layer. The team uses Airflow to connect disparate systems, transform, enrich, and store data for supporting AI and analytics workloads, while ensuring reliable and scalable pipelines. Adonis outlines four best practices for teams looking to scale their Airflow usage: dependency mapping, anomaly detection, tiered data quality monitoring, and keeping business intelligence dashboards simple and focused. The team uses a "carbon layer" architecture and leverages technologies like Apache Spark and Apache Kafka, with Airflow serving as the orchestration backbone that enables faster innovation with AI and analytics while managing legacy system complexity.