In Episode 79 of Razorleaf’s Stay Sharp podcast, Agentic AI: Rewiring Digital Workflows, co-hosts Jonathan Scott and Juliann Grant are joined by Rob Ferrone, known as the Product Data PLuMber—note the PLM reference—for his expertise in “fixing PDM leaks and blockages across the lifecycle to improve information/data flow.” Together, the trio tackles the buzziest topic in artificial intelligence right now: agentic AI.
While AI is about creating machines that can reason and learn in a way that would normally require human intelligence, agentic AI makes that intelligence active. Rob describes four As that characterize agentic AI: active, meaning it takes action, makes decisions, and influences things; assorted, referencing multiple types of AI agents; autonomous, because they can act on their own; and adaptive, in that they’re always learning and bettering themselves instead of needing to be fed more data. Agentic AI is getting the hype, Rob says, because “companies are actively looking to use these in a way that they couldn’t necessarily use [regular] AI for, because now they can actually get it to do familiar things—like the things that their staff is doing.”
The Next Revolution
Juliann, Jonathan, and Rob agree that the reason they’re talking about this topic now is because it’s new and big—and we need to understand it. The discussion is topical, because agentic AI is finally the AI that can do some of the things people do. And when Rob is asked what he sees it being used for, he responds, “The answer is absolutely everything you could imagine.”
Rob goes on to explain that agentic AI is “almost like having access to an additional workforce that is superhuman.” Juliann adds that it’s going to be able to help us “identify things we can’t see that quickly—the trends, the problem-solving that it can do in microseconds.” More, it can tell us what we’re forgetting or don’t know to think about when considering big-picture questions. “This is going to affect every single part of the business anywhere you’ve got humans,” Rob says. “Anywhere you’ve got people making decisions or having to pull together information and then act on the information they get. That has the potential to be transformed.” In short, agentic AI could truly revolutionize the way people work.
The Challenges of Getting There
The idea that AI might replace workers is a primary concern for many in the manufacturing industry. Rob has a different perspective, citing the World Economic Forum’s prediction that more jobs will be created than lost in the future and their suggestion that we will become “more creative in our jobs and will be leaning into our uniquely human skills more and more.” Of course, that will take some learning and different approaches. “I think what’s most important for everyone to have at this time is two things: growth mindset and curiosity,” Rob says. “If everyone has that, then I think we’ll be able to adapt to whatever comes.”
But the single biggest hurdle for companies who want to employ agentic AI, Rob cautions, is “the simple nuts and bolts of good quality data and connected flows across different systems. That has got to be the bedrock of a company’s ability to leverage agentic AI.” It’s the “garbage in, garbage out” philosophy. “If they haven’t got the sources of information or if the data’s not good, you can imagine what kind of decisions are going to be made,” Rob says. “Because for all the intelligence that you get with AI and AI agents, ultimately they are informed by the information that they consume.” As Jonathan notes, it all comes down to needing to train your AI systems with the right high-quality data.
Organizations also need to understand that implementing and trusting AI, especially agentic AI, is going to take significant effort. Months to years of effort. Rob says, “It’s a lot of people. A lot of money. And it all starts with the vision, what do you want to do with it? What’s the intent of how you’re going to apply this? And there’s obviously business strategy. Do you do small experiments? Do you provide all of this technology to the team and let them have a go and kind of figure out what they can do with it?” He adds, “There’s a lot of work to implement this technology. There’s a lot of potential. And there’s a lot to be excited about.”
Learn More About How Agentic AI Might Change Product Manufacturing
The full podcast contains more discussion and details on a variety of topics, including the potential agentic AI has to change the fundamental way businesses operate, specific use cases for agentic AI in manufacturing organizations, where to start when you want to implement agentic AI, how it could impact product innovation, and more.
Be sure to check out Stay Sharp Episode 79: Agentic AI: Rewiring Digital Workflows and join us each week for a new podcast.
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