A (2:45)

Doesn't shut the machines down.

B (2:46)

In manufacturing, it's mission critical. And you're usually dealing with, you know, the industries I came from in either the nuclear, chemical, or pharmaceutical. You're either throwing away batches that cost millions of dollars or you're doing something that would Create a safety event. So I think in a manufacturing environment that availability becomes really kind of the paramount thing is you got to keep things up and operational and you really can't afford downtime. So you're really running four five nines all the time in manufacturing.

A (3:21)

Okay, so I had a big getaway. Yeah. So how do you build cyber resilience in that kind of environment? How do you build it not only to the software platforms, but in manufacturing worldwide? And how do you think AI is going to impact that in the future?

B (3:36)

Yeah, I mean, the resiliency is about, you know, redundancies, you know, in both power and in our case, kind of controllers, like right down to the IO level. So having redundancy across, you know, anything that could fail. So you find your single points of failure and then you build redundancy and automatic failovers between those. So that if any one thing can't take you down, that's kind of just generally how you have to think about it. And then, you know, in that even though you're building all these redundancies in, you got to plan for the worst case scenario. So then you start thinking about recovery. The way that I kind of looking at cyber resilience is closing the front door. Don't make things easy, but expect that if you had a nation state attacking you, they're probably going to get in. So now you got to really focus on can you recover quickly of your critical assets. So do you have good backups? Have you tested those? Can you recover within your recovery time objectives? Right. And recovery point objectives. Right. So that you can bring things back up. So that's kind of how we focus on things in Rockwell is what's Tier one, Tier zero critical infrastructure. Your tier one applications that you have to run and then can you bring those back in a state that they were before? So having immutable backups, things that couldn't be, you know, violated or adulterated.

A (5:05)

I wonder how many industries have to think about a. Another country attacking them, for example.

B (5:11)

So, yeah, I mean, I think that there are certain industries that would have nation state actors. We, we support critical infrastructure. So we're worried about that not only for ourselves, but for our customers that are running critical infrastructure structure. Water, wastewater, of course, the Defense Department, and then, you know, power industry, we support all those industries. So our, you know, internal operations need to be tight so that our customers can be.

A (5:39)

Yeah, redundancy is critical, obviously. Yeah. How are you leveraging AI, machine learning and predictive analytics in your operations and customer offerings?

B (5:50)

Yeah. So AI is A great topic for us. It's embedded in every part of our kind of strategy and our go to market and our products and services. But we're also using it internally. We're a manufacturer ourselves, so we use it in our own manufacturing and then we're using it at the enterprise level for, you know, your typical productivity enhancements and that sort of thing. I think one of the most, you know, interesting use cases for us was something that we actually won the CIO award here for is our factory AI solution in one of our our manufacturing facilities in Singapore. This is helping with optimization of the production lines, building quality in helping onboard new engineers and new production employees, helping them with the testing, that sort of thing, and then embedding assistance in as something's happening in the manufacturing environment, guiding operators through the recovery process and what's happening in the process itself.

A (6:51)

So AI actually acts as an assistant with onboarding people, for example.

B (6:55)

Yeah, yeah. So if you think of a production employee, it would typically take us maybe six months to onboard someone in our assembly lines to get them up to speed about how to assemble our products. Well, there's sometimes a high turnover rate there and then, or you get a manufacturing, you get a big demand, so you have to onboard more people. Onboarding, you know, taking six months, we've been able to bring that down to, you know, several weeks or maybe a month and a half by using AI assistance that kind of guide them through the process and then combining that with AR&VR to give them kind of visuals on how to do the assembly. So, you know, I think this applies for many jobs, right. Where you can onboard people quicker into the competency that they need to perform the task.

A (7:45)

I gotta be honest, I've never thought of that as a use for AI before. So that's remarkable. What's one of the cultural shifts you've led at the company and especially in the IT organization that you're really proud of?

B (8:01)

I think the biggest cultural shift for the IT organization has been making sure that they knew that we are just not providing back office kind of operations. Yes, those are important. They're mission critical from that standpoint, but that the IT is a part of the strategy of the company. So, you know, I always, you know, try and remind them that it is the business of Rockwell and the business of Rockwell is it. Our stated strategy is bringing the connected enterprise to life as a company. What that means is the integration of the IT world in the OT world. So things that run in the factory, the things that run in the enterprise. Well, we're in, you know, it's part of that strategy. So embedding that kind of cultural mindset that it is part of the ongoing strategy. Our products and services are embedded in what we provide to customers. This is how we grow revenue, this is how we grow market share as a company. So just really making sure that they're part of the strategy, not just enabling it. Yes, we enable it, but we're also part of the future strategy of the company.

A (9:12)

So you guys are at the center of industrial digital transformation. How has your own IT organization evolved to support mission internally and for customers?

B (9:25)

Yeah, I mean, the evolution is kind of grounded in what I just talked about is being part of the strategy is we're not only providing the underlying system, transactional systems to operate, but the customer interface. We've done a lot of work on that customer experience part. So something internally we call our demand to renew and growing our subscription services and annual recurring revenue. So just as few as five, six years ago, our annual recurring revenue is less than 1% of our total revenue. Today it's over 10% is annual occurring revenue. That provides a lot of capability for the company. But it also required a shift in our operating model as a company from selling through a hardware, through a distribution channel. Now our product portfolio is expanded to more software, more services, more software as a service and then that kind of go to market motion is very different when you're selling subscriptions or annually occurring revenue, which required an overhaul of kind of all the transactional systems, the salesforce organization adding more software capabilities both within IT and in our product units. So we interface that way. My group also has our IT group, also has a group for data analytics and insights. So sometimes they're creating solutions that we use in our own factories. This is part of what we call our Rockwell on Rockwell program. We become the first and best customer where we're kind of drinking our own champagne, eating our own dog food in the company. And then those solutions that we create, and many of them these days are including AI as a bigger component of it, become showcases for customers. They come in and see how we're operating our own manufacturing. And then they say, well, we think we have something similar in ours. So I think that really embeds it. And then sometimes we're working directly with customers on bespoke solutions in the AI space. And then those sometimes get adopted into our product portfolio or into our solutions and services organizations that get resold to other customers.

A (11:46)

It makes a lot of sense. I mean, you're showcasing it within Your own environment, they can see how it works. I get that. What is smart manufacturing really mean today? And how is Rockwell helping customers move from concept to execution?

B (12:04)

Yeah, so smart manufacturing is all about this industrial 4.0, or moving up the maturity curve from really augmenting kind of your operations to semi autonomous to eventually autonomous things that run by themselves. So you think of, you know, a self driving car. Well, you could have a self driving factory, fully autonomous. So we're helping customers think about that roadmap and that journey of maturity from, you know, really level one through level three and level five would be kind of autonomous factory. Most of those, you know, totally autonomous factories are operating in like the semiconductor industry. Other industries are well below that. But we're having a lot more conversations in every industry about how do they become this factory of the future, how do they build that kind of capability? And it's really the convergence of several technologies that are available now. It's a combination of marrying physical AI up with causal AI and agenic AI. So you think about starting the order, moving it through into production, and then having it wind up on a physical device like a robot. Right. And those autonomous robots then can move things to their production line and kind of have everything kind of work together on a feedback loop that operates the manufacturing process autonomously. Okay,

A (13:37)

I want to move on to skills, especially in your industry. What skills are most in demand for your IT and digital teams right now and how are you attracting or developing them internally?

B (13:49)

Yeah, we've seen quite a transition on skills. First it was kind of having more software skills, having more cloud operations. Now you're starting to interject all the AI capabilities into it. We've built up kind of data science kind of capabilities, machine learning capabilities over the year, but now everything's moving towards AI, agents, agency AI being able to leverage the large language models and then marry that up with what I've talked about earlier, the causal AI that happens in manufacturing and the physical AI controlling kind of the physical devices, building of digital twins. Right. So that's another technology that we see as very important for this autonomous operations. So hiring people that have first off literacy and AI, but then can build up, you know, kind of fluency. And this is not just for IT people going forward. It's also going to be for all of our functional areas in the company as well as our product development groups who are also embedding it. So, so AI is kind of embedded in every level of our strategy going forward, in our products and services, our customer experience, but then in Our enterprise operations.

A (15:10)

And a lot of people have never heard the term physical AI, but when you say that you're talking about AI ingesting information data from physical devices.

B (15:19)

Yeah. And vice versa. Pushing down, having agents tell that physical device, a robot, what to do and then the robot being, having its own AI so that it can autonomously navigate through kind of a complicated manufacturing floor, bring goods to the line, bring move goods throughout the line and then bring it back to the warehouse and then do warehouse management with it.

A (15:42)

And I'm sure IoT has a lot

B (15:44)

to do with that. Absolutely, it does.

A (15:48)

Well, I want to end on a light hearted question. So this can be personal or professional, but you have a favorite gadget right now or application that you're playing with.

B (16:00)

You know, a favorite gadget. I'd say my favorite, you know, pastime is looking at all the new technology that comes out every week and seeing what has been kind of overcome, you know, from week to week. Right. The, you know, GPT5 just got released, you know, a couple days ago. So, you know, kind of you playing with those tools and looking at the capabilities and then what, what did it take out of the portfolio that was there? That's a little bit of my favorite pastime is these things are moving so fast and keeping up to pace with it is then, you know, what other tools am I, you know, deprecating? Because now there's new capabilities in these large language models.

A (16:41)

I lied. I have one more follow up because that generated a thought in my head. What do you think of GPT5? It's promising a lot. It's probably promising more accurate responses, fewer hallucinations. What do you think of it so far?

B (16:58)

I think it's, it's pretty, it's been pretty powerful from the limited times I've done it. I would say that from my experiences where people get tripped up is not maybe following the rules of prompting correctly. Right. So there's a great prompting guide out there. There's the whole guide on GPT5. I think sometimes people just start using the tool without understanding the constructs that work best with it.

A (17:23)

Right.

B (17:23)

So I'm pretty bullish on, you know, the capabilities continuing to improve. But you gotta follow some, you know, good practices to get the best out of it. That's what I would say makes sense.

A (17:36)

Christopher, thank you. Thank you so much for being here and giving me some of these insights. I really appreciate them. They were great. Yeah. And I hope you enjoy the rest of the show.

B (17:45)

Yeah, it's been great, great show and I enjoy talking about this topic, so thanks for asking.