人工智能的人性化优势：在受监管的医疗保健系统中建立信任、安全和价值

The Human Edge of AI:Building Trust, Safety and Value A strategic framework for responsible AI governance MARIE FLANAGAN, Director, Product, Regulatory & AI Governance SME, IT Design & Development, IQVIAMIKE KING, Senior Director, Product & Strategy, IQVIAJANE REED, Director, Life Sciences, IT Design & Development, IQVIA Table of contentsExecutive summary1Key points2The hybrid future: AI as amplifier, not replacement3The human-machine partnership model3Why humans remain essential4Governance as trust infrastructure5The competency challenge: preserving institutional knowledge8Strategic responses to the competency cliff9AI literacy as regulatory compliance10Three dimensions of AI literacy10Building literacy programs that work11Ethics and beneficence: The patient-centric imperative12Four ethical principles for healthcare AI12Measuring patient-centric ROI13The implementation reality: Common challenges14Practical deployment strategies15Measuring success and driving continuous improvement17Practical implementation: Case vignettes18Case vignette 1: Turning off self-learning18The pragmatic solution18Case vignette 2: Manufacturing quality control partnership19The optimal partnership19Conclusion: The path forward20Five pillars for responsible implementation20Seven strategic imperatives for success21The ultimate measure: Patient benefit21Next steps: Advancing your AI governance readiness22 Executive summary As AI transforms healthcare, organizations face a critical challenge: harnessingAI’s capabilities while preserving the human expertise, ethical judgment, and The pharmaceutical, medical device and in-vitrodiagnostics industries stand at an inflection point. AIpromises revolutionary advances, yet without adequate AI should amplify human judgment,not replace it. Success demands ahybrid intelligence model where This paper provides Quality Assurance and RegulatoryAffairs (QARA) professionals and clinical leaders aroadmap to navigate AI transformation while maintaining •AI literacy is now a regulatory mandate:The EUAI Act and FDA guidance require organizations todemonstrate workforce competency, transformingtraining from operational choice to compliance Key points: •Human-in-the-loop is non-negotiable:Regulatorsworldwide mandate meaningful human oversight,making it the trust layer that legitimizes AI in clinicalsettings. This requirement reflects irreplaceable •Governance builds competitive advantage: •Ethics and beneficence define ROI:Healthcare AIsuccess must be measured by patient outcomes andsafety improvements, not automation speed or cost Transparency, validation and auditability create marketdifferentiation and accelerate regulatory approval.Organizations with mature governance frameworks The regulatory landscape is evolving rapidly. WhileAI capabilities advance exponentially, regulatoryframeworks struggle to keep pace. Organizations must •Preserving institutional knowledge is critical:AsAI automates routine tasks that traditionally providedlearning opportunities, organizations risk losing tribal The hybrid future: AI as amplifier, not replacement The most fundamental insight from healthcareAI deployment: AI exponentially expands humanexpertise rather than replacing it. Across medical device This partnership model represents a fundamentaldeparture from traditional automation. Whereautomation has replaced human labor in repetitive tasks, Pharmaceutical manufacturing AI transforms quality control, process optimization andregulatory compliance. Predictive maintenance preventsequipment failures before they impact production.Real-time monitoring detects process deviations The human-machine partnership model Medical device innovation and development AI enables new depth in product development and post-market intelligence. Organizations mine manufacturingrecords, service logs, clinical notes and user feedbackacross millions of data points to uncover patterns Clinical trials AI accelerates patient identification by analyzingelectronic health records for enrollment criteria matches.Protocol optimization uses historical data to predictrecruitment challenges and optimize design. Safety PMS represents perhaps the most transformativeapplication. Traditional systems operate retrospectively:events occur, reports are filed, analysis happens, The regulatory imperative reinforces this reality. U.S.FDA guidance, EU Medical Device Regulation andemerging global AI-specific frameworks worldwidemandate meaningful human oversight. This requirement Why humans remain essential Three capabilities distinguish human judgment frommachine intelligence in healthcare: clinical expertise forcontextual interpretation, ethical reasoning for navigating Governance as trust infrastructure Effective AI governance isn’t regulatory overhead— it’s strategic infrastructure enabling innovationwhile protecting patients and ensuring compliance. VALIDATION: Proving performance and safety Rigorous validation proves AI systems pe