How Philips is actually scaling AI
Builders by Proxify13 Touko

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

Tämä jakso on lisätty Podme-palveluun avoimen RSS-syötteen kautta eikä se ole Podmen omaa tuotantoa. Siksi jakso saattaa sisältää mainontaa.

Jaksot(77)

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

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 Heinä 29min

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

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 Heinä 22min

How Slack actually uses AI at work

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 Heinä 47min

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

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 Kesä 49min

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

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 Kesä 41min

Why most Software Engineers are preparing for the future wrong

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 Kesä 50min

This data science mistake is killing AI projects

This data science mistake is killing AI projects

Data science, AI, spam detection, fraud prevention, MLOps, and machine learning teams are reshaping how product companies build trust at scale. In this episode of Builders, Liniker Seixas, Senior Staf...

27 Touko 43min

The tech behind IKEA: secrets to global loyalty success

The tech behind IKEA: secrets to global loyalty success

Discover how IKEA's Head of Engineering Loyalty, Jip Koudjis, is transforming global loyalty systems to deliver personalized experiences at scale. Learn how IKEA consolidated 11 local programs into on...

27 Touko 43min