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Rockwell’s Blake Moret on urgency, AI adoption, policy shifts and why manufacturers must become learning organizations 

 

David Brousell (DB): I’m David Brousell, the founder of the Manufacturing Leadership Council, the digital transformation arm of the National Association of Manufacturers.

I’m here with Blake Moret, the chairman and CEO of Rockwell Automation.

Congratulations, Blake, on becoming chair of the NAM this year. From your position as chair of the NAM as well as CEO of Rockwell, what is your sense of the state of the industry at this point in time? And where do you see digital transformation in manufacturing and smart manufacturing?

Blake Morret (BM): To begin with, the importance of manufacturing has never been more widely recognized by, governments around the world, but in no place, more urgently than in the U.S. And I think that’s a very good thing. I think that manufacturing is at the core of the American economy.

The magic multiplier of jobs outside of just direct manufacturing, is often under underestimated. And so the recognition by the government, by, you know, our population, is very encouraging to see that.

How do you increase the manufacturing in the U.S.? I think it’s going to be important to recognize that in a place with relatively high labor costs, to be competitive with other strong companies around the world, you have to include the technology with that. So smart manufacturing, advanced manufacturing techniques are going to be really important. And of course, artificial intelligence is a part of that as well. And policy that creates a conducive environment is going to be really important as well.

The NAM is in an amazingly important place because, on the other end, there’s a lot of uncertainty where tariffs going where our, regulations are going to lead us? And the NAM, with its understanding of these issues and the aggregate power of the thousands and thousands of members, has an opportunity to really make a difference.

DB: If we all work together.

BM: Yeah

DB: If we all orchestrate together all those things you just talked about.

Why Smart Manufacturing is Accelerating

DB: Let’s drill a little bit into smart manufacturing.

One of the main conclusions of your 10th annual state of manufacturing or smart manufacturing report was that, due to global risks, including tariffs, supply chain disruptions, the industry seems intent on accelerating its adoption of smart manufacturing.

Yet we know that many manufacturers, deal with a lot of challenges about adopting smart manufacturing, whether it’s the legacy systems, the cost, budget constraints, understanding how to deploy new technologies, etc.

What pace do you think the industry is poised to move at this point in order to accelerate their adoption of smart manufacturing? And do you think we can get past just incremental improvements? Is there something you see, perhaps, on the horizon that could enable us to make a leap?

BM: I think there is a heightened sense of urgency about moving faster and complementing continuous improvement, incremental improvements, which remains very important.

People are still needed. The idea is to give them superpowers with some of the new technologies.

 

 

It has to be a part of the culture, but also being willing to compare all the other options that are out there, other competitors who have found different ways to do things, different internal techniques that can change the game, so to speak.

I think of, you know, the importance in our own culture of being willing to compare ourselves against all the other choices that a stakeholder has, whether it’s a customer, an employee, an investor, to increase the speed of decision making, which is especially important in a, you know, long standing company like, like Rockwell.

And then making sure you have a steady stream of new ideas from both the lifers in the organization, as well as, people with new perspective.

DB: The right ten incremental improvements could add up to a leap.

BM: When we look at our productivity, when we look at the way that we slice our engineering and development budgets, it’s going to be a mix of incremental improvements, fixing things, adding new functionality that’s important to a specific customer, but it’s also about the big leaps as well.

In our own roadmaps, adding more software, infusing artificial intelligence, in some cases needing to create products and software from the ground up to be able to have modern code bases, to be able to expand still further into the future. And sometimes incremental approaches just aren’t enough.

But I think there is that sense of urgency. Tariffs have increased the need for speed, so to speak. Being able to move around your manufacturing footprint, to be able to add resilience into your operations, the agility that’s required for that. And sustainability is still important and being the best steward of water, air, gas, electricity and steam, because in the end, that’s a measure of efficiency.

DB: That’s a lot of balls to juggle.

BM: It’s a lot of balls to juggle and to prioritize and to weave it into something cohesive.

Leadership in a Time of Constant Change

BM: And that’s an important point in that, just like the technologies we’re talking about that move from automation to autonomy using artificial intelligence to help machinery actually learn how to be more performant, organizations have to be learning organizations.

The things that I thought were going to be priorities when I moved into this job have changed quite a bit over the time. And, you have to be comfortable with that pace of change.

DB: You have to be comfortable with being uncomfortable.

BM: Yeah, there is a certain amount of that.

The Future of Industrial Operations

DB: Let’s dive a little bit into the future you just mentioned. You’ve been talking about and Rockwell’s been talking about the future of industrial operations. And in your articulation of that future, you have talked about what you call intelligent autonomous systems. What’s the extent of autonomy that you envision coming into the industry? Do you think the manufacturing companies are going to be embracing a fully lights out model? Do you see a more of a hybrid coming in where certain functions will be completely autonomous, but others that have more criticality will not be?

BM: I get asked this a few times, as you can imagine.

DB: Yeah.

BM: I think it’s still a human-centric view of the future of automation in factories. People are still needed. The idea is to give them superpowers with some of the new technologies. But there are going to be very few truly light-out factories.

People are still needed. But to be freed up from repetitive physical labor—moving a heavy thing from one place to another—I think those are some of the opportunities that are ahead for us. Particularly in higher labor cost countries like the U.S., being able to take an engaged and enabled workforce, people who are trained to do a good job and want to do a good job because they like the organization that they’re working for, and they like the work they’re doing, complemented by the technology. That’s really the winning hand.

And we see that, across multiple industries. Some industries have had more technology in them. They’re further along in that journey. Others are really at the at the front end of that. But it’s the ability to make improvements to meet those companies and those industries where they are to bring it in, to be able to pay a lot of attention to the change management that’s required so that operators recognize that this can create more meaningful work—it’s not just being used blindly to reduce headcount. For managers to understand how the technology can be best used and to have a thoughtful plan.

Rockwell’s in the automation and the efficiency business, but I fully expect we’ll have more people at the end of 2026 than we enter 2026 with, because we’re going to be more competitive as we use this technology, and we’ll be able to do more of the things that we’re already doing, will be able to enter into new lines of business—and that all requires people.

From Artificial to Augmented Intelligence

DB: Perhaps we should call it augmented intelligence.

BM: I think it’s a good way to frame it because, again, that concept of human-centric automation and an approach to this is really important to keep in mind. A lot of the benefits of AI are going to be simplifying technology that remains very advanced, but to bring it together in a way that you can interact with it, that people can interact in the technology with natural language, for instance, rather than having to know the arcane programing languages that were developed half a century ago.

And I think those are really exciting opportunities for advancement in the whole interaction between people, operators, technicians and the technology itself.

DB: We can’t have one of these conversations without talking a lot about AI. It’s so present in our lives now.

You’ll have to spend more time than you think on change management.

 

 

We did a big report that we released in May called Shaping the AI-Powered Factory of the Future. And one of the key findings in that study was that 68% of the respondents said they believe that AI will be essential to their competitiveness and growth as we head toward 2030. I think that’s quite a statement. And to me, it meant that a lot of companies are looking at this to propel themselves forward. There’s a bandwagon effect happening. As all these companies start to get their toes and their feet and their ankles and their legs into AI, where do you think they’re going to get the most value from AI? And what do you think the competitive differentiators are going to be for companies as we all embrace AI and it becomes kind of like a high school diploma.

BM: At a high level, across multiple industries, the importance to add additional resilience and agility and sustainability to your operations are really going to be important.

Having people who are comfortable with the tools, who also know the workflows in their individual areas of responsibility—whether it’s in a certain business unit, your coding, your applications, it’s in back office functions, human resources, things like that, in marketing—it’s going to be applying artificial intelligence to workflows to simplify them, to give them more impact in the organization.

What I don’t want, as our people become more literate with AI, is to just go out on fishing trips, you know, to see what turns up. I want them to first identify what are problems that have been vexing their particular areas for a long time, and how can we apply a toolset which includes AI to identify that and then to bring it, in our case, with multiple centers of excellence, to be able to then decide, okay, what’s the best tools, either things that we ourselves have created or what’s already out there in the open market, and to try to standardize as much as possible. But to be able to work with folks who have the pattern recognition to say, “Okay, you’re trying to do this. We’ve done something very similar over here,” so that we can do it in a common way.

But there is an accountability. How is this going to show up?

In the organization, you know, there’s a certain amount of productivity that I expect already this year to come from AI. And going forward, it will be a mix of the quick hits, so to speak, and the moonshots that are going to completely change some of the ways that we do things. For customers, it’s applying AI at all levels of the technology stack, from vision AI to mobile robots to scheduling software that includes AI and then bringing it together into a coordinated, highly orchestrated system.

DB: I almost thought you were going to say the word architecture, how important this is going to be with AI.

BM: Yeah, I think it is. I mean, we talk about the three underpinning areas of technology—and I’m talking about in factories today—is a software-defined automation architecture, it’s the use of artificial intelligence, and then it’s robotics.

DB: At MLC we call AI a “pervasive technology,” and we mean it in a couple of ways. One is what you mentioned that AI was going to find itself into every system, on the factory floor at the EBS level, at the ERP level, at the PLM level, CRM level, everywhere. At the same time, it touches every piece of what the NAM does.

How Policy Can Enable AI

DB: There’s kind of an important question about what steps can policymakers take to create a supportive framework for manufacturing and AI that drives innovation, efficiency and all the things we as an industry need to advance? How do we do that at a policy level?

BM: Let me step back a minute. Before talking specifically about AI, let’s talk about the environment that has to be created for durable and persistent support of manufacturing, in general.

The first important step with getting some certainty around tax, statutory tax rate, incentives for new investments with the One Big, Beautiful Bill, I think that’s really important and giving that level of certainty has been an absolute positive.

In any change, explaining the “why” is really important.

 

 

 

The work on permitting reform and streamlining regulations, I think those are important areas. Additional certainty with respect to tariffs, of course. And then, the final one and maybe most important long term is workforce—being able to provide purpose-built education that doesn’t require necessarily a four-year degree or even a two-year degree, to be able to be really effective.

And that bridges to the specific question about artificial intelligence, in that the workforce, the education, helping companies understand how to set up a functioning infrastructure and governance to make sure that as new ideas are created, you have knowledgeable people who can translate that into action, who, again, can draw from the tool sets that are appropriate for their enterprise to be able to make it reality, but also to have the governance to make sure that safety, you know, privacy, all the things that you know, are brought up as potential risks are looked after and including the disruption of certain roles are changed through the increased use of AI. How do you make sure that that doesn’t destroy the culture of a company? Because all of us know that that culture is really, really important.

DB: Change management takes on a new dimension, doesn’t it?

BM: You’ll have to spend more time than you think on change management.

DB: And cyber will be a key piece of this too.

BM: That’s absolutely right, because the bad guys are using AI as well.

DB: Yeah. Any tool could be used for good or bad, right?

BM: Right.

Reducing Complexity in an AI World

DB: You continue to emphasize that manufacturers should continue to emphasize reducing complexity. We’re building layers and layers and layers of IT and OT technology in our companies, and now the wave of AI is going to come in as well. That takes an incredible amount of orchestration, architecture, real hard thinking about how you’re going to do this as a company.

How do manufacturers deal with all those requirements and yet reduce complexity at the same time when it seems like inexorably things are getting more complex?

BM: Well, first of all, it takes a commitment to that and to really devote that effort and the right expertise to develop that thoughtful approach.

And I think it then requires the convening of stakeholders, whether it’s your machinery suppliers, your subject matter experts who are on the plant floor who know, what happens and what can go wrong and what contributes to the best output, bringing them all together. Sometimes it requires, you know, a handful of trusted consultants as well to come together and look at a specific problem and how we can apply these things to create the best outcome.

Again, don’t go at it with a fishing trip with a bunch of tools and to look at what shows up. It’s better to go say, “Here’s a specific problem that I have in a location, and let’s put the right team together so that it’s endorsed with the people who have to keep it running and are responsible for the production.”

DB: Yeah, let me kind of bubble a little bit. Don’t worry about a strategy right away. Get some experience, do some experimentation.

BM: Yeah. Play yourself into shape to some extent.

DB: Yeah I like that.

BM: But that simplification is really, really important because then you’re not as dependent on individual heroics to keep it running.

DB: Yeah that’s quite a challenge.

Leadership Through Change Fatigue

DB: We have a lot of challenges in an industry we’re facing, but it’s so exciting too. I find this whole thing with AI so exciting—what’s going to happen to the industry in the next 10 or 15 years.

Which kind of takes us back to the question about leadership, because leadership, we’ve always felt, is the key to digital transformation.

It’s not the technology, it’s leadership. It’s changing the organization to take advantage of the technology. It’s changing the culture. And all those “soft issues,” so to speak.

Going back to the Rockwell report, the Rockwell report says that effectively managing people and resources and dealing with resistance to change are some of the biggest issues facing manufacturing companies.

And it’s not slowing down, and it’s led to what the report called “change fatigue.” How can manufacturers overcome these challenges and keep their teams motivated, sustain momentum? Is it just a question of stamina, or is there some technique to it too?

BM: In any change, explaining the “why” is really important. To be sure, we’ve had a lot of externally generated challenges and requirements for change. Recently it’s been things like, the COVID pandemic. It’s been supply chain shortages. Overstock in certain industries. Tariffs. And so there have been a lot of things that we didn’t ask for necessarily, but that have come in. But then we see other aspects requiring change like the adoption of artificial intelligence in a thoughtful way.

So explaining the why and making sure that you’re doing that early and often, and leadership really understands the why and takes the time throughout the organization, not just at the highest level, because a lot of times where this falls down is kind of at that middle layer, you know, the manager/director level, do they really understand or are they are they a part of the formulation of the plan for how these things are going to be implemented?

You can’t just be doing [AI] as a labor of love. It’s got to be done for impact.

 

 

And so taking more time than you think you need to, usually turns out to be very, well spent time. To instantiate that and then to frequently check in because there’s always going to be a course correction. You’re not going to get it 100% right ahead of the implementation and so being able to course correct so that you keep those key stakeholders on board.

I mean, those are some general things with it. I think in the specific case of artificial intelligence, having a certain amount of expertise is really important. We made an acquisition of a company called Kalypso a few years back, and it brought in a tremendous amount of data scientists. It was further augmented by an acquisition of a company called Knowledge Lens after that because we needed to kind of jumpstart that internal capability. And we had people who understood these concepts, but we weren’t going to be able to scale as quickly as we needed to. And so as we are now entering a phase where these things are being deployed more broadly, we’ve got the right talent base in our own operations as well as what we’re talking to customers about.

Organizing Around the AI Opportunity

DB: That’s a great privilege to be able to bring in that talent at that scale.

BM: Yeah.

DB: And probably a lot of companies that can’t do that, particularly the small and medium sized manufacturers, it could be more of a challenge. But what you’ve been talking about has provoked in my mind a question about I often ask myself about AI and manufacturing companies, and it comes down to how best to organize around the opportunity. How should we do that? You know, do we appoint a team? Do the manufacturing companies need a chief AI officer? Do they need their HR departments, as you’re talking about, to have a specific campaign for AI talent? How best to organize around the opportunity?

BM: Everybody’s approaching it in a little different ways, but where we’ve seen certain measure of success is you do have some centralized centers of excellence, if you will. We have a center of excellence that’s concerned primarily with the use of AI in what we offer to customers based on the business that we’re in, hardware, software, and so on. And then we have within our IT organization, a clearinghouse for people looking to use business systems internally to be able to maximize, you know, the use of AI for efficiency.

But within each of the functions and businesses, we require a certain amount of internal expertise because these are the people who really understand the workflows particular to that area, whether it’s human resources or marketing, finance and so they’re expected to work together. We have a very large community of practice of people from both kind of the centralized and distributed areas of expertise. And they get together regularly to share best practices, to talk. It’s allowed us to move at pace.

And then back to my earlier comment about ownership. It’s got to show up in our productivity targets. It’s got to show up in terms of market share gains in terms of the products that we’re offering.

So you can’t just be doing this as a labor of love. It’s got to be done for impact.

DB: If they haven’t already, Wall Street will recognize it and build it into their valuations.

BM: Yeah.

DB: Right?

BM: Well, they’ll see it because it’ll show up in greater growth as well as profitability.

DB: Yeah that’s the end game for sure.

Approaching the Future

DB: Looking forward into the next five years, ten years, etc., what advice would you offer manufacturing operational leaders as they try to embrace a future that’s characterized by AI and autonomy, which many could feel is disruptive?

BM: I think you have to learn enough about it to understand what the potential is as well as, what you have to manage in terms of potential adverse impact.

But most succinctly, you have to be a learning organization.

DB: Yeah

BM: You have to be a learning organization.

DB: Yeah. Continuous learning.

BM: That’s right.

DB: Well, thank you very much. A most interesting conversation, I’m sure we’re going to do it again soon in the next year or so and we’ll see what has changed. And hopefully the industry makes some progress.

BM: Absolutely. It’s been a pleasure, David.

DB: Yeah. Thank you.

BM: Thank you.  M

 

About the Author:

 

David R. Brousell is founder, vice president and executive director of the Manufacturing Leadership Council

 

Pull quotes:

People are still needed. The idea is to give them superpowers with some of the new technologies.

You’ll have to spend more time than you think on change management.

In any change, explaining the “why” is really important.

You can’t just be doing [AI] as a labor of love. It’s got to be done for impact.