This episode captures Walid Mehanna's perspective on how Merck KGaA has approached enterprise AI adoption through a federated strategy that prioritizes people over technology. The core message is that successful AI implementation requires building organizational capability across three dimensions - people, processes, and technology - rather than seeking a single transformative solution. Walid argues that companies must establish a broad foundation of AI literacy (exemplified by their internal MyGPT tool reaching 25,000 users) before pursuing specialized applications, while maintaining human accountability to prevent complacency. He emphasizes that AI works best when it's treated as an experimental, iterative capability distributed across the organization rather than controlled centrally, with success depending on persistence through the inevitable J-curve of initial productivity drops. The conversation reveals how a large multinational navigates the practical realities of AI deployment - from managing regulatory complexity across different geographies to making pragmatic build-versus-buy decisions - while maintaining focus on the fundamental principle that AI should augment human expertise rather than replace human judgment and responsibility.
This episode captures Walid Mehanna's perspective on how Merck KGaA has approached enterprise AI adoption through a federated strategy that prioritizes people over technology. The core message is that successful AI implementation requires building organizational capability across three dimensions - people, processes, and technology - rather than seeking a single transformative solution. Walid argues that companies must establish a broad foundation of AI literacy (exemplified by their internal MyGPT tool reaching 25,000 users) before pursuing specialized applications, while maintaining human accountability to prevent complacency. He emphasizes that AI works best when it's treated as an experimental, iterative capability distributed across the organization rather than controlled centrally, with success depending on persistence through the inevitable J-curve of initial productivity drops. The conversation reveals how a large multinational navigates the practical realities of AI deployment - from managing regulatory complexity across different geographies to making pragmatic build-versus-buy decisions - while maintaining focus on the fundamental principle that AI should augment human expertise rather than replace human judgment and responsibility.
(0:00) Intro
(0:29) How AI is Used at Merck
(2:18) AI Applications Across the Value Chain
(4:31) Challenges and Risks of AI Implementation
(5:35) Federated Approach to AI Prioritization
(6:44) Future AI Use Cases and Data Challenges
(10:38) Building and Partnering for AI Solutions
(15:11) AI in Drug Discovery and R&D
(26:47) Quickfire
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