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It’s not that AI is going to take over all conceivable jobs in manufacturing, necessarily. Experts think instead that AI-enabled devices will work with humans to increase productivity—and maybe even solve tricky problems that consumers increasingly care about, like how to be more green.

Andreas Eschbach, writing in Forbes, posits that AI can (and will) help unlock a plant’s “hidden value”—that is, its unrevealed and untapped capacity—by making informed decisions that expand productivity, improve sustainability, increase flexibility, and bolster the workforce. These outcomes might stem from actions like predicting equipment failure and supply chain disruptions, spotting bottlenecks, and identifying solutions to these problems and others.

Sounds good! So what’s standing in the way? Poor data quality is one answer, including “missing data points, broken or miscalibrated sensors, incomplete data mappings or dictionaries, incompatible systems, architectural limitations, slow access speeds, and insufficient understanding of existing sources.” Adding to this long list, we could mention old systems and weak data governance that must be addressed.

Solutions are available. McKinsey recommends companies adopt an “agile, data-centric approach” to improving data quality, such as by deploying teams of data scientists, engineers, and data experts who can identify and fix any problems standing in the way of AI doing its job. Eschbach, too, observes that for AI to work, it’ll need humans working alongside it—the machine and the person, joined hand in byte.

Discussion Questions:

  1. How will AI transform the manufacturing industry?
  2. What are the obstacles standing in the way?
  3. What can be done to make AI more effective, in the manufacturing context?

Sources: Andreas Eschbach, “How Humans and AI Can Untap New Manufacturing Capacity,” Forbes, January 6, 2023; “4 Ways Artificial Intelligence Could Transform Manufacturing,” WEBforum.org, January 9, 2023; “Clearing Data-Quality Roadblocks: Unlocking AI in Manufacturing,” McKinsey.com, January 20, 2023

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