艾昆纬-生命科学MDM中的代理人工智能（英）

White PaperAgentic AI in Life Sciences MDMA new era of data stewardshipSOWJANYA BUKKAPATNAM TIRUMALA, Senior Director, Product and Strategy, Global Master Data Management, IQVIAFRANCESCA D’ANGELO, Director, Information Management Offering, IQVIATable of contentsExecutive summary 1The transformative role of agentic AI in MDM 1Comparing agentic AI to traditional MDM approaches 2Key evaluation criteria for AI-driven MDM solutions 3Data quality management 3Data profiling and cataloging 3Governance and compliance 4Scalability and performance 4AI-readiness and integration 4Continuous data stewardship and self-optimizing governance 5Intelligent rules management 5Continuous refinement through self-optimizing governance 5Automation guided by human expertise 6A new era of always-optimized MDM 6References 7About the authors 8iqvia.com | 1The transformative role of agentic AI in MDMAgentic AI is revolutionizing Master Data Management (MDM) by deploying autonomous agents that collaborate to execute multi-step processes and solve complex data challenges with advanced reasoning — often powered by large language models — thus functioning as a dynamic digital workforce that brings intelligence, autonomy and real-time decision-making to MDM. This innovative paradigm enables routine tasks such as data cleansing, matching, enrichment and governance checks to be performed round-the-clock with minimal human intervention, fundamentally transforming MDM from a manual, reactive process into a proactive, self-driving system. For life sciences companies burdened with vast, varied and highly regulated data — from clinical trial results to patient records and product information — agentic AI offers a game-changing solution by rapidly harmonizing data and streamlining processes like regulatory report compilation, ultimately freeing human experts to focus on strategic initiatives while ensuring data is managed efficiently and accurately.Executive summaryLife sciences organizations are at the cusp of a transformative shift: Integrating agentic Artificial Intelligence (AI) into Master Data Management (MDM) is redefining how customer and product data are managed. Unlike traditional AI systems that require constant oversight, agentic AI operates autonomously: setting objectives, making decisions and acting on them with minimal human intervention. For pharmaceutical and biotech companies that grapple with intricate datasets, stringent regulations and high stakes, this innovation promises unparalleled improvements in data quality, operational speed and overall process agility.Early adoption in the pharma/healthcare sector — where approximately 23% of organizations had implemented AI agents as of 2024 — illustrates the momentum of this shift.1Industry analysts predict that by 2028, nearly one-third of enterprise software will feature agentic AI capabilities, up from almost none in 2024.2This white paper outlines the role of agentic AI in modernizing MDM programs, contrasts it wit