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    Implementing AI in manufacturing is a great idea, but the implementation process can get tricky. 

    Industry Week said, "If implemented successfully, these systems can greatly improve quality control and optimize costs. Although many manufacturers are trying to implement such systems into their workflow, very few have managed to reach full-scale production."

    Why do projects get stuck?

    AI projects are often tested in controlled environments.

    But, as Industry Week noted, that's not how the real world works. 

    "When pushed into the real world with real-world constraints like variable environmental conditions, real-time requirements, and integrations with existing workflows, proof of concept often breaks down."

    How to implement AI successfully

    Successful implementation takes collaboration. 

    Machine Design said, "Since AI needs a lot of data to work effectively, you will need a lot of brain power and experience to know common and special cases, anomalies, and where different tools could provide the greatest benefit with a focus on root cause analysis. In short, human intelligence is needed to guide what artificial intelligence should be doing and not doing."

    It could be beneficial to realistically look at how much you're able to take on as a company. Bringing in outside professionals that specialize in AI could be the best option for your business. 

    No matter what you choose, be sure to create a clear strategy and work together to get everyone on board. Communicate through the entire implementation process to ensure that it happens smoothly and successfully. 

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