How Philips is actually scaling AI

About this episode

Jonas Dieckmann discusses how Philips is scaling AI through innovative data strategies in health tech.

Data Engineering, AI Experimentation, Health Tech, and Data Platforms are reshaping enterprise innovation. In this episode of Builders, Jonas Dieckmann, Global Manager of Data Intelligence & Team Lead of Data Engineering at Philips, explains how one of the world’s largest health tech companies is scaling AI through cross-functional collaboration, domain-driven data platforms, and rapid experimentation. Why do so many enterprise AI initiatives fail — and what is Philips doing differently? Jonas shares: How AI squads accelerate innovation inside large organizations Why short AI experiments lead to faster business impact The evolution from centralized platforms to data mesh architectures How metadata and data lineage are becoming critical for AI success The biggest challenges in healthcare data and governance What makes a great data engineer in the AI era The trends shaping the future of data and AI If you’re building data platforms, scaling AI teams, or navigating enterprise transformation, this episode delivers practical insights from the frontlines of global health tech. 🎧 Subscribe to Builders for more conversations with leaders shaping the future of AI, engineering, and…

People in this episode

Guest: Jonas Dieckmann

Topics covered

• AI scaling
• health tech
• data engineering
• data platforms
• enterprise innovation
• cross-functional collaboration
• rapid experimentation

Keywords

• AI
• data engineering
• health tech
• data platforms
• data mesh
• enterprise AI
• innovation
• metadata
• data lineage
• governance

Mentioned in this episode

Organizations: Philips, Data Engineering, AI, Health Tech, Data Platforms, enterprise

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