Context-first data is essential for making AI trustworthy, scalable, and regulator-ready in the biopharmaceutical industry. While AI adoption has grown significantly across research, development, and manufacturing, many organizations struggle to achieve measurable business value because their data lacks the structure, context, and governance needed for reliable AI use. Successful AI initiatives depend on data that is well-organized, semantically enriched, traceable, compliant, and managed throughout its lifecycle. Key elements such as data provenance, semantic context, and strong governance help ensure transparency, consistency, and regulatory credibility. By creating a foundation of high-quality, context-rich data, organizations can move beyond isolated AI pilots and deploy enterprise-sca

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