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 Valuein Regulated Healthcare Systems 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 contents Executive 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, andinstitutional knowledge essential to patient safety. This framework synthesizesIQVIA’s insights for responsible AI governance in regulated healthcare. The pharmaceutical, medical device and in-vitrodiagnostics industries stand at an inflection point. AIpromises revolutionary advances, yet without adequategovernance, poses significant risks to patient safety andcompliance. The challenge isn’t whether to adopt AI buthow to implement it responsibly. AI should amplify human judgment,not replace it. Success demands ahybrid intelligence model wheremachine precision enhances clinicalexpertise, ethical reasoning andregulatory interpretation. This paper provides Quality Assurance and RegulatoryAffairs (QARA) professionals and clinical leaders aroadmap to navigate AI transformation while maintainingthe human judgment healthcare demands, balancinginnovation with safety, efficiency with oversight andtechnological capability with ethical responsibility. •AI literacy is now a regulatory mandate:The EUAI Act and FDA guidance require organizations todemonstrate workforce competency, transformingtraining from operational choice to compliancerequirement. Organizations must prove staffunderstand AI limitations, can recognize bias andexercise appropriate oversight. This mandatecreates both compliance obligations and strategicopportunities for capability development. 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 irreplaceablehuman capabilities in clinical judgment, ethicalreasoning, and regulatory interpretation. AI shouldamplify these human strengths, never replace them. •Governance builds competitive advantage: Transparency, validation and auditability create marketdifferentiation and accelerate regulatory approval.Organizations with mature governance frameworksenjoy faster market access, stronger clinician trust andreduced regulatory friction. The pillars of institutionalknowledge — clinical judgment, ethical judgment andregulatory interpretation — remain the gold standardthat AI must enhance, not replace. •Ethics and beneficence define ROI:Healthcare AIsuccess must be measured by patient outcomes andsafety improvements, not automation speed or costreduction alone. The principle of beneficence demands AIsystems demonstrably improve patient care, not merelyavoid harm. This patient-centric measure of successcreates necessary discipline in resource allocation. The regulatory landscape is evolving rapidly. WhileAI capabilities advance exponentially, regulatoryframeworks struggle to keep pace. Organizations mustwork within current standards while remaining flexibleenough to accommodate future guidance. Successrequires starting with proven governance approachesand adapting systematically as requirements crystallize. •Preserving institutional knowledge is critical:AsAI automates routine tasks that traditionally providedlearning opportunities, organizations risk losing tribalknowledge and contextual expertise that decades ofexperience have built. This competency cliff threatenspatient safety when less experienced staff lack judgmentto appropriately question AI recommendations orrecognize when escalation is warranted. The hybrid future: AI as amplifier, not replacement The most fundamental