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Unlock AI's Full Potential: The Power of FAIR Data
Session Chair(s)
Anuj Uppal, MS
Vice President, Life Sciences Transformation
Campana & Schott, United States
AI underperforms when data isn’t machine-actionable. This talk shows how FAIR + open standards turn fragmented R&D data into fuel for LLMs and analytics—via a mini-rubric, case studies, and a 90-day roadmap to lift AI-readiness.
Learning Objective : Apply a mini-FAIR rubric to one dataset/document to diagnose AI-readiness and summarize 2–3 priority gaps; Select the standards (PIDs, metadata, vocabularies) that unlock a target AI use case (e.g., RAG, model reuse); Draft a 90-day plan—roles, metrics, checkpoints—to raise FAIR maturity and improve AI outcomes.
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