What's Up with Tech?
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With over three decades in telecom and IT, I've mastered the art of transforming social media into a dynamic platform for audience engagement, community building, and establishing thought leadership. My approach isn't about personal brand promotion but about delivering educational and informative content to cultivate a sustainable, long-term business presence. I am the leading content creator in areas like Enterprise AI, UCaaS, CPaaS, CCaaS, Cloud, Telecom, 5G and more!
What's Up with Tech?
Intelligent Automation: How Zebra Technologies is Revolutionizing Frontline Operations
Interested in being a guest? Email us at admin@evankirstel.com
The manufacturing floor and warehouse operations of tomorrow won't simply be automated—they'll be intelligent, adaptive, and collaborative. This fascinating conversation with Andy Zosel, Senior Vice President of Intelligent Automation at Zebra Technologies, takes us deep into the evolution happening at the intersection of AI and physical operations.
Andy reveals how Zebra's journey in machine vision and computer vision laid the groundwork for today's AI revolution, creating systems that don't just capture data but derive meaningful insights from physical environments. We explore the critical balance between human capability and machine precision, with Andy sharing a surprising revelation: "The more we attempt to automate processes historically done by people, the more impressed we are with human capabilities."
The discussion illuminates practical approaches to automation implementation, including the critical "crawl, walk, run" methodology. Rather than making dramatic leaps, Andy advocates for visibility-first strategies that identify high-impact opportunities before deploying solutions. This measured approach helps organizations overcome the common challenge of knowing where to begin their automation journey.
We also explore fascinating technological convergences, including multimodal capabilities that fuse RFID with machine vision and 3D sensing to create unprecedented operational visibility. These integrated approaches are particularly valuable as organizations shift from traditional high-volume, low-mix manufacturing to more agile environments requiring high-mix, variable production.
Whether you're just starting to explore automation possibilities or looking to enhance existing systems with the latest AI capabilities, this conversation provides a practical roadmap for creating collaborative environments where humans and technology amplify each other's strengths. The future of work isn't about replacing people—it's about creating intelligent partnerships that leverage the best of both worlds.
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Hey everybody, Really excited to dive into the world of automation and digitization with a leader in the field of the enterprise, particularly frontline operations at Zebra Technologies. Andy, how are you?
Speaker 2:I'm doing well, Evan. How are you?
Speaker 1:I'm great. Thanks so much for joining. Always intrigued to learn more about what's happening at Zebra. Before that, maybe introduce yourself a little bit about your journey and your team at Zebra.
Speaker 2:Before that maybe introduce, yourself a little bit about your journey and your team at Zebra. Yeah, so it's exciting times, certainly in the industry, and I've had a lot of wonderful things in my past that have kind of prepared me for the role currently as Senior Vice President of Intelligent Automation at Zebra. I spent most of my career in industrial automation and machine vision with various companies and prior to Zebra was running a couple of business units in that space. I've joined Zebra, I've been there a little over a couple of years now two years with Zebra and today I have responsibility for what we call intelligent automation, which includes three business units of machine vision, robotics and RFID.
Speaker 1:So this must be the most exciting time in your personal professional career, given what's happening with AI and maybe we'll start with customers, given all the advances you're making with the latest and greatest AI tools and models. I mean, how are your customers using AI to kind of improve visibility efficiency in all of these different environments in which they work, you know, manufacturing, warehousing, supply chain, hospitals and on and on?
Speaker 2:Yeah, that's a great question and of course it has many layers. Like AI, has a lot of places it's influencing our industry I mean, certainly even before all of the awareness came in the last couple of years to AI and generative AI. Ai was used quite extensively within machine vision and computer vision for several years and we were an early investor in that space, and so AI in that context has been really critical for advancing the application use cases within our customers' environments for how they can inspect product, how they can think about all the different inspections and quality improvements that they can make with camera-based systems. And then most of our portfolio is oriented towards kind of digitization or creating intelligence around physical objects. You can think, obviously, the simplest example being barcodes and creating that data.
Speaker 2:And of course we create data and then our customers have to, in most cases, figure out what to do with that data. And of course we create data and then our customers have to, in most cases, figure out what to do with that data. And AI has really been a boon to them to help to figure out what to do with the data, how to take the next best action, and certainly we're helping them with a lot of capabilities around that, both generative AI and then agentic AI, et cetera. So it's it's. It's been a really exciting time, both kind of evolution of some of the computer vision AI technologies as well as how do our customers take the data that that we're creating and get a hunger for more data right. I mean, if you're, if you're using AI, there's almost a no, there's an unending appetite I guess is the best way to put it for data, and we're in the business in a lot of cases of helping our customers with creating data.
Speaker 1:Amazing. So boosting productivity is the name of the game. I feel more productive than ever, but when it comes to you and your customers, it's more about collaborative AI. You know, helping manufacturers improve productivity and quality, so that's not a trade-off. So do you have any examples or anecdotes or stories on? You know delivering real business results?
Speaker 2:Yeah, so I think, if you look at productivity enhancements and capabilities around that, it comes down to understanding your operation and having visibility of where some of the bottlenecks are so that you can apply the tools correctly, because AI is, as you mentioned, quite the tool to apply in those areas and in a lot of cases, there's people involved in those processes in addition to machines and processes, et cetera. So a lot of our systems are built in a way that we're collaborating and bringing the people into that kind of digital infrastructure and so, whether it's a production line where you may be using something like machine vision or code reading to track and trace or to inspect the product, there's still, a lot of times, a person that needs to take action against that, whether it's to improve the maintenance of the machine or to adjust the product line. So bringing that whole kind of pieces together and leveraging AI to optimize that is a big part of what our customers are doing today with our products and technologies.
Speaker 1:Amazing. And speaking of bringing tech together, working together is a challenge. Right, interoperability, interworking I mean you have machine vision solutions, rfid products, endpoints, robotics solutions, rfid products, endpoints, robotics. I mean, how do you think about getting everything to work together seamlessly and make sure the tools are as simple to use as possible for your end users and customers?
Speaker 2:Yeah, yeah, I think there's always a balance between kind of depth and breadth of capabilities and then ease of use, and the ideal thing with innovation is that you give depth and breadth of capabilities but then you still make them easy to implement, easy to use, and that's always where innovation goes. You think about a world that's becoming more complex and more capable. You can think of things like camera-based systems that have more and more resolution, that have different ways to image, including non-visible light, et cetera. So things are opening up from a capability perspective, but then you still have to implement it. So how do you help customers choose the right product or even deploy the right product? A lot of that innovation can be, you know, going back to AI, you can implement some AI to help make those decisions and help or help guide the customer in that regard, and then thinking of it always from a customer first perspective, right, you know what is their experience going to be like, what truly problems are they trying to solve and how do we get them to that solution faster?
Speaker 2:You asked about interoperability and certainly you know we have a pretty broad technology portfolio zebra, um and we've established, you know, a very uh strong footprint in um, barcode reading and, um, you know, mobile computing and printing and kind of general data capture technologies. We're leveraging a lot of the experience in those areas of digitizing work to help our customers migrate from that digitizing to automating and kind of helping them on that journey as best we can, putting things in the context of things that they've known and comfortable with and using. You know where be it. You know, transitioning from a handheld barcode reader to a fixed mount barcode reader, to a machine vision system and using some common language, common APIs that really help our customers, whether our customers be the end customer or the system integrator, the solution builder in between, such that, as you know, if you're working with Zebra you've got some familiarity along that journey and that's been a big focus for our teams is how do we help our products? You know even acquisitions that we've made all come into kind of a common customer experience and framework.
Speaker 1:That makes sense. And, speaking of customers, you must see various challenges, roadblocks that they face in adopting intelligent automation, any common themes that you hear again and again as far as helping them overcome those challenges, those challenges.
Speaker 2:Yeah, I think one of the big challenges with automation is where to start. I think everybody knows that they need to automate. I think everyone knows that automation can bring benefits, and but all projects are not created equal, obviously. And in a lot of cases, traditional industrial automation there was typically a very large capital expense required to deploy and so the hurdle rate or the return on investment you know to deploy that would be quite high. And so that's where intelligent automation brings hopefully you know a more accessible automation level, things that can be deployed with less implementation.
Speaker 2:You can think of some of our AMRs and the way that our autonomous mobile robots are deployed in an environment with some of the capabilities to self-map and do things like that that enable a lower upfront cost, and then in some cases even the cost is more of a operating expense than an upfront capital expense.
Speaker 2:And then in other ways, you know, we have opportunities to work with our customers around visibility into the process. So you know automation is great but you know again, not all things are created equal. Maybe there's a piece of the process that is by far the most expensive or labor intensive, or even you know their team members or associates don't like to do that part of the process. Those can be more visible if you really understand what's happening in your operation. So it gives you those clarity of where your baseline is and where your choke points are in the process so that you can choose the right things to automate, choose the right projects to automate, which of course, if you're starting from a known baseline it's always easier to prove or to know where to fix the classic kind of Pareto analysis and start from there from an automation perspective.
Speaker 1:Yeah, it makes sense and you've been known through your career kind of, as always, looking ahead, trying to look one or two steps ahead. It's a little difficult these days as things are moving, it seems, at light speed. How far ahead do you try to look over the next year or two, three, as far as big trends and what? What are some of the trends you're excited about or following, tracking moving forward?
Speaker 2:Yeah, yeah, I think I think there is a lot of change and opportunity in that change in in our industry. I think, fundamentally, there are, you know, still some kind of first principles maybe of automation or process or operations that still hold true around. You know, thinking about how to make processes more lean, more efficient, more friendly to customers. I think you know a lot of our customers are now being requested to be agile themselves because their market is so dynamic. So how do you help them create a system that, especially when you think about automation systems, traditionally they were very good at creating extremely high volume, low mix environments. How do you create automation that can be adaptable to relatively high mix, low mix environments? How do you create automation that can be adaptable to relatively high mix, low volume?
Speaker 2:And then you know things like multimodal capabilities. So you know the fusion of RFID and then machine vision and even barcode and different ways of data capture and what that provides from environment visibility capability. You know, just you know it's the classic if you can't see it, you can't fix it. You know. And providing that additional visibility into an operation. You know it's a big part of, for example, you think about Industry 4.0, and a lot of that is about IoT and visibility, and we're still on a journey there where a lot of industries and a lot of operations managers to act on that visibility using traditional mindsets and tools, but also bringing in AI and some advanced generative tools and then taking that to the third place of truly making the changes and automating it. So a lot of opportunities both in the multimodal data capture kind of the visibility and analysis, but then also the implementation of change that's flexible and adaptable to the future state in that regard. So that's kind of how I see it in those three areas from an automation perspective. Interesting.
Speaker 1:And of course there's a lot of discussion, sometimes heated debate, about the role of automation and people. And it's pretty clear there's some lot of discussion and sometimes heated debate about the role of automation and people, and it's pretty clear there's some sort of balancing act to be had. But what do you think that partnership will look like over time and how do we get the balance right?
Speaker 2:Yeah, it's a great question. I think the more we attempt to automate processes that historically were done by people, and and maybe you know, maybe this is is just me as you go through your career and understand more and more the, the capability of the human, uh, from even just a pure physical you know, perception, and and and articulation, everything the more we are impressed with the capabilities that that people provide. Right, the flexibility, the ability to you know, grasp and and feel and visually perceive, um. So there's a high degree of respect that I think you gain if, if you've been involved in physical automation for a long time, uh around just how capable an individual human or associate is in an environment, um, so you understand that it's it's it's going to be a big challenge to just think that you know all the tasks, and even the difficult tasks that are being done by humans today can be easily automated. That being said, like I said, the the technology has been advancing rapidly and and there certainly is a lot more possibility today, especially when you pair it with the ai piece. So I think where we really look at it is how do we take away the tasks that are either significant productivity limitations or things that are kind of the dull and dirty and dangerous, the things that we really don't necessarily people don't want to do in the future anyhow, are by far the best opportunities for automation, and being able to understand where those are at in an operation is is key, and that goes back to the visibility piece that we talked about earlier.
Speaker 2:Um, but then I think there is in a lot of operations, especially in a high mix, high variability operation, a flexibility and a creativity that humans provide that is very difficult to replicate, no matter how advanced the AI or how advanced the automation. So being able to create systems that have that collaborative capability, that can have both humans and automation in the same environment working collaboratively, has a huge value for customers, both at the end state of that automation journey, but also as they go along that automation journey and think about a transition from maybe a fully manual process to a fully automated process. There's going to be a it's hard to just make the hard switch. So how can you take take that journey into automation with with making things collaborative and and allowing for parts of the process to be done by humans, enabled by wearables and other things like that, and other parts of the process to be fully automated?
Speaker 1:Yeah, it's interesting. You talked in the past about the crawl, walk, run approach to things and I guess things like wearables are certainly a great first step and initial crawl, but there doesn't seem to be a playbook or a blueprint or a guide to advanced AI automation or agentic. Any advice to companies on this journey and how to kind of get it right and not skip too many steps in this process.
Speaker 2:Yeah, and you're right. I mean generally because the state of the art is advancing so quickly around agentic AI and um, what is possible, you know, what may not be possible now could easily be possible, you know, next week or next month or next year, um, so I think it's it's cautious You'd be cautious to make you know hard statements about what's not, what you shouldn't try or what you shouldn't do. I think fundamentally it still comes back make you know hard statements about what's not, what you shouldn't try or what you shouldn't do. I think fundamentally it still comes back to you know what are the key areas of your business that are, you know, either restraining agility or restraining productivity, or or what are the things that can have the greatest return on investment and, I think, to have visibility of your process and understand it. You know there's kind of some no regrets implementations there that you know I've talked about in the past how automatic data capture, which is quite mature, still has a really important place when it comes to implementing.
Speaker 2:Even you know, advanced technologies and things like agentic AI. I think clearly we see the most opportunities and things that already are highly digitized, so things that are almost pure digital environments like software coding, and some of those areas are really getting the most productivity gains from generative and agentic AI. But I do think, as we tie physical automation into those spaces and make it adaptable, that there will be all kinds of opportunities. But it's difficult to predict where that limit exactly is because it's definitely a moving benchmark and I guess you know, back to your crawl, block one. It starts with visibility, it moves to, you know, uh, finding those places in the process that are the most, um, clearly have a return, and then, uh, you know, starting to implement in those areas and see if you can gain a return on investment from that regard.
Speaker 1:Amazing. So you guys are busy, to say the least, maybe a little quieter in the summer, but you have a busy back half of the year. What are you looking forward to in terms of industry events, company events or anything else on your radar as we head into the end of the summer and busy fall season?
Speaker 2:Yeah, yeah, I think I think we we have a lot of um exciting capabilities that we introduced um this last spring around some of our collaborative robot solutions. Uh, we introduced a new way for people and carts and robots to work in a in a warehouse environment and all coordinated um. You know, that solution continues to gain significant traction in the market for us and and we're continuing to add capabilities to that solution. You know, certainly, when you start to think about agents in a um orchestrating agents in an environment, um, you can think about the physical environment as well as the digital environment, and there's so many things that you can do with those type of solutions.
Speaker 2:I think the multimodal thing that I mentioned earlier about bringing together technologies such as RFID with computer vision, machine vision, 3d sensing we acquired a business earlier this year that was really focused on 3D cameras, so we introduced a new scan tunnel concept that includes various technologies and integration of those technologies from Zebra in automated scanning kind of over-the-conveyor type solution, automated scanning kind of over the conveyor type solution. So those type of advances and foundational platforms that can help our customers. We're going to continue to invest in those areas and certainly, as you mentioned you know, continue to invest in AI and those opportunities. So a lot of exciting things in the pipeline, that some of those will certainly come out later this year and into next year from from the Zebra business.
Speaker 1:I can't wait to see it all unfold, and it's exciting times. Thanks for joining and sharing just an update on the vision and the mission.
Speaker 2:Yeah, thank you, evan. It was great to catch up and look forward to our next conversation.
Speaker 1:Likewise and thanks everyone for listening and watching and sharing and check out our new TV show Attack Impact on Bloomberg and Fox Business. Thanks everyone, Take care.