AI in Manufacturing: Do’s and Don’ts for Smart Adoption

Artificial intelligence (AI), especially Generative AI (GenAI), is creating significant buzz in manufacturing, with many companies eager to invest.

According to Rockwell Automation’s 9th Annual State of Smart Manufacturing Report, 83% of companies plan to implement AI this year, making it the top area for investment in the next 12 months.

As a manufacturing leader, you’re likely exploring AI’s potential to transform your operations. But with so much hype, how do you separate reality from fiction?

In our latest article, “AI in Manufacturing: Do’s and Don’ts for Smart Adoption,” TBM’s CEO, Bill Remy, and Board of Directors member, Gary Freburger, provide practical advice on successfully integrating AI into manufacturing while steering clear of common pitfalls, including the danger of overconfidence.

In this article, you’ll discover:

• How to set realistic expectations for AI implementation
• Strategies to leverage your existing data effectively
• Ways to balance AI capabilities with human expertise

The AI Journey: From Small Steps to Big Wins in Manufacturing

AI is a powerful tool for enhancing decision-making in manufacturing, but it’s not a replacement for human expertise and execution. It can identify improvement opportunities, but its effectiveness hinges on the quality and organization of data. Poorly managed data leads to unreliable AI analytics, making proper data management essential. To ensure successful AI adoption, manufacturers should take a phased “crawl, walk, run” approach—starting with basic analytics and performance metrics, then gradually scaling AI once a solid foundation has been built and its value proven.

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