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 industrial data and AI educator and strategist. He specializes in Industrial AI, IIoT, Unified Namespace, Digital Twins, and Industrial DataOps, helping manufacturing leaders implement and scale Smart Manufacturing initiatives.

Kudzai shares this thinking through Industry40.tv, his independent media and education platform; the AI in Manufacturing podcast; and 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. Recognized as a Top 15 Industry 4.0 influencer, he currently serves as Senior Industry Solutions Advocate at HiveMQ.