The future advantage of AI in life sciences will not come from having the most data, but from having the most trusted, governed, and AI-ready data. Many organizations face fragmented data across systems, vendors, and formats, creating challenges with confidence, speed, governance, and responsible AI adoption. Preparing for AI requires strong foundations including clear metadata, common definitions, data lineage, quality controls, and shared governance. A modern data strategy should focus on improving the data experience by making assets, ownership, quality, and availability transparent. Organizations need flexible, modular approaches that integrate existing systems while reducing friction. By building connected and trusted data ecosystems, companies can accelerate insights, improve decisio

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