Generative AI is reshaping life sciences but many pilots fail, with over 70% never reaching production due to unrealistic expectations, poor workflow integration, difficulty proving accuracy, and weak use cases. Success depends on targeting high-value areas like automating repetitive tasks, analyzing large text datasets, and accelerating coding. Cost and risk hinge on data complexity, compute requirements, user adoption, and privacy safeguards. Emerging trends include small language models, agent-based systems, and seamless workflow integration. IQVIA’s Healthcare-grade AI and agentic approach aim to balance business impact, cost, and risk for scalable, compliant deployment.

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