How Philips is actually scaling AI

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 innovation.
#DataEngineering #AI #HealthTech #DataPlatform #DataMesh #Philips
Chapters
(00:00) How Philips Is Driving Data Innovation in Health Tech
(01:24) Jonas Dieckmann’s Journey Into Data & AI Leadership
(02:44) The Biggest Challenges of Data Platforms in Healthcare
(05:27) Why Health Tech Data Is More Complex Than Most Industries
(08:07) Inside Philips’ AI Squad Strategy for Innovation
(13:15) How Philips Chooses AI Use Cases That Actually Matter
(16:36) Why Fast AI Experiments Lead to Better Results
(22:46) The Shift From Centralized Data Platforms to Data Mesh
(28:35) Data Governance and Ownership in a Data Mesh World
(30:37) What Future Data Platforms Must Support for AI
(33:01) Why Metadata and Data Lineage Are Becoming Essential
(35:26) What Separates Great Data Engineers From the Rest
(39:58) How Philips Evaluates Talent for Data & AI Teams
(45:30) The Most Exciting Trends in Data and AI Right Now
(47:39) The Biggest Mistakes Companies Make When Scaling AI
(50:03) Jonas Dieckmann’s Vision for the Future of Data at Philips

Det här avsnittet är hämtat från ett öppet RSS-flöde och publiceras inte av Podme. Det kan innehålla reklam.

Avsnitt(79)

The Last AI Mile with Zimply.ai's Jesper Fredriksson | Proxify Talks

AI is rapidly evolving from a powerful tool into a transformative force for organizations and society.In this keynote, Jesper Fredriksson explores the current state of AI, the accelerating pace of tec...

27 Juli 22min

The hidden security risks of AI agents, with Ali Leylani | Proxify Talks

I agents are becoming more capable and more autonomous. But as they gain access to tools, memory, and company data, they also introduce new security risks.In this Proxify Talk, Ali Leylani, Co-founder...

24 Juli 13min

Why AI adoption fails with Louise Vanerell & Carl Carlheim-Gyllensköld | Proxify Talks

AI implementation is easy. AI adoption is hard.In this episode, Louise Vanerell and Carl Carlheim-Gyllensköld explore why so many AI initiatives fail to create lasting organizational value despite str...

15 Juli 29min

Closing the AI Gap, with Atlan AI’s Rocío Bachmaier | Proxify Talks

How do companies move beyond AI pilots and actually scale AI across their organization?In this keynote from Proxify HQ, AI strategist and transformation expert Rocío Bachmaier shares practical lessons...

8 Juli 22min

How Slack actually uses AI at work

AI is changing technical roles faster than ever. But does that mean customer-facing engineers are becoming obsolete?In this episode of Builders, Lee Haynes sits down with Liliana Lindberg, Lead Soluti...

1 Juli 47min

The end of traditional companies? How AI Is reshaping leadership, hiring & work

AI, organizational transformation, leadership, hiring, AI native companies, the future of work, organizational design, and AI adoption are changing how businesses operate.In this episode of Builders, ...

23 Juni 49min

Why most AI projects fail in production (and how Amazon solves it)

Data Engineering, Machine Learning, AI, Data Trust, AI Governance, and ML Ops are transforming how companies scale intelligent systems.In this episode of Builders, Deepak Yadav, Engineering Leader at ...

16 Juni 41min

Why most Software Engineers are preparing for the future wrong

Leadership, engineering teams, AI in software development, responsible tech, career growth, and the future of work. How do great engineering leaders build high-performing teams in the age of AI? In th...

3 Juni 50min