<?xml-stylesheet type="text/xsl" href="https://emersonexchange365.com/cfs-file/__key/system/syndication/rss.xsl" media="screen"?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:slash="http://purl.org/rss/1.0/modules/slash/" xmlns:wfw="http://wellformedweb.org/CommentAPI/"><channel><title>Part 1: Why AI in Life Sciences Must Be Grounded in Validated Execution</title><link>/industries/lifesciences/b/life-sciences-blog/posts/part-1-why-ai-in-life-sciences-must-be-grounded-in-validated-execution</link><description>The common digital strategy playbook is: unify the data, layer on AI, and drive enterprise-level insight. The strategy sounds compelling in its simplicity. And for some industries and some use cases, it can work. But in regulated life sciences manufacturing</description><dc:language>en-US</dc:language><generator>Telligent Community 13</generator></channel></rss>