November 7, 2025

Finding Opportunities for AI Application in Manufacturing

Manufacturing leaders are familiar with physical waste; scrap, rework, and inefficiencies in production.

But digital waste is the hidden inefficiency thatโ€™s just as costly.

It includes:

๐”๐ง๐ฎ๐ฌ๐ž๐ ๐ƒ๐š๐ญ๐š: Factories generate massive amounts of data, but much of it is never analyzed or leveraged for decision-making.

๐ˆ๐ง๐ž๐Ÿ๐Ÿ๐ข๐œ๐ข๐ž๐ง๐ญ ๐ƒ๐š๐ญ๐š ๐‡๐š๐ง๐๐ฅ๐ข๐ง๐ : Engineers waste time manually entering, cleaning, or searching for information that should be automated.

๐’๐ข๐ฅ๐จ๐ž๐ ๐ˆ๐ง๐Ÿ๐จ๐ซ๐ฆ๐š๐ญ๐ข๐จ๐ง: Key insights are trapped in different departments or legacy systems, preventing AI-driven optimization.

Digital waste silently drains resources, increasing operational costs while blocking AI from delivering its full potential.

Once manufacturers recognize digital waste, the next step is identifying where AI can generate the biggest returns.

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Watch/Listen below:

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Kudzai Manditereza

Founder & Educator - Industry40.tv

Kudzai Manditereza is an Industry4.0 technology evangelist and creator of Industry40.tv, an independent media and education platform focused on industrial data and AI for smart manufacturing. He specializes in Industrial AI, IIoT, Unified Namespace, Digital Twins, and Industrial DataOps, helping digital manufacturing leaders implement and scale AI initiatives.

Kudzai hosts the AI in Manufacturing podcast and writes the Smart Factory Playbook newsletter, where he shares practical guidance on building the data backbone that makes industrial AI work in real-world manufacturing environments. He currently serves as Senior Industry Solutions Advocate at HiveMQ.