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Meet Michael Lynch, CEO at Praxie
"How do you practically apply artificial intelligence? I think that's the core question that most manufacturers are asking themselves," says Michael Lynch, CEO at Praxie, in our new podcast episode. "AI is the second step. The first step is getting digital, because you can't use AI unless your stuff is digital. So if you think about a pragmatic roadmap, it's get digital, get all that stuff out of Excel sheets and paper, and build those workflow processes."
Praxie is an AI-powered software platform that advances digital transformation for discrete and process manufacturing companies. Once a company digitizes its documents and processes, the AI built into their workflows can give feedback and insights about issues seen on the factory floor, or generate an action plan by tapping into a large language model. Or, AI can extract insights from a company’s data, identifying root causes of problems.
However, for manufacturing organizations to reap the full benefits of AI, they have to ensure they're underway with their digital transformation first. Two of the challenges to digital transformation are cost and time: how expensive your infrastructure providers will be and how long it'll take to implement the solution. But another challenge is the human element, because if you try to implement new digital processes that are different from what you currently have, they won't be adopted.
In This Episode
How can manufacturers overcome the hurdles to a successful digital transformation, and use AI to improve their processes to make them better execution leaders? Listen to our conversation with Michael Lynch to learn more about how AI is transforming manufacturing today and how it will continue to do so in the future.
Topics
- How Michael made his way from Broadway to video games to leading an AI software company in manufacturing.
- Why manufacturing companies need to digitize first before they can then practically apply AI to help solve operational problems.
- The two big challenges that manufacturing companies face in their digital transformation.
- Best practices for managing your data, and why data cleanliness will affect your outcomes.
- Examples of how manufacturers can use AI to improve their production, increase efficiencies, and lower scrap through more effective management.
- Some of the indicators that tell a business they're ready for a digital transformation.
- What a "manufacturing plant of the future" may look like with its augmented environments and computer vision.
