Here's what they don't tell you about manufacturing AI:

Getting a pilot to work is the easy part. Getting it to work everywhere, every day, with every shift?

That’s where most initiatives stall.

Scaling, and more importantly, sustaining, AI success means dealing with legacy equipment, inconsistent data, cybersecurity concerns, and deeply rooted human habits, all across global operations.

In the latest episode of the AI in Manufacturing podcast, I sat down with Jonathan Alexander, Global Manufacturing AI and Advanced Analytics Manager at Albemarle Corporation

‍Jonathan and his team didn’t just escape the trap of pilot purgatory, they scaled AI across their global operations and delivered real, sustained impact.

e unpack how they did it, and what it takes to build AI-driven transformation that lasts.

Here’s the outline of our conversation:

⇨ Key Data Challenges in Implementing AI at Scale

⇨ Data Contextualization for Analytics and Decision Making

⇨ Data Architecture & Interoperability

⇨ Standardization & Scaling of AI Applications

⇨ Driving Sustained Action from AI Insights

⇨ Sustaining AI Adoption & Value Creation on the Plant-Floor

⇨ Change Management & Culture

Watch/Listen now 👇

- YouTube: https://lnkd.in/deUnsqS2

‍- Spotify: https://spoti.fi/3748AXf‍

- Apple: https://apple.co/3lY5vhl

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