Transformation on an industrial scale at Rockwell Automation

The business of Rockwell Automation is rooted in IT. As one of the world’s largest providers of industrial automation and digital transformation technologies, Rockwell, with headquarters in Milwaukee, has a market cap of over $40 billion and customers in over 100 countries. With those kinds of proportions, and a legacy going back over 120 years, industrial transformation and cultural adjustments are crucial to ensure a longstanding and competitive future. And at its center is SVP and chief digital and information officer Chris Nardecchia.

“I think the biggest cultural shift for the IT organization has been making sure they knew we’re just not providing back-office operations,” he says. “Yes, those are important and mission critical, but our stated strategy is bringing the connected enterprise to life as a company.”

Of course, building up capabilities in data science, ML, and increasingly agentic AI is integral to that success, as well as being able to leverage LLMs and synergize it all with causal and physical AI. And hiring people with literacy of AI is one thing but making sure they can build up fluency is the real test.

“This isn’t just for IT people going forward,” he says. “It’s also going to be for every functional area in the company as well as our product development groups. So AI is embedded in every level of our strategy going forward regarding products and services, customer experience, and enterprise operations.”

And as manufacturing evolves and gets smarter, Nardecchia makes sure he and his team are fixed to the maturity curve, from augmenting operations and being semi-autonomous, to eventually being purely autonomous. “Think of a self-driving car,” he says. “Well, you could have a self-driving factory. So we’re helping customers think about that roadmap of maturity. Most totally autonomous factories operate in the semiconductor industry. Other industries are well below that, but we’re having more conversations about how to become factories of the future, and how to build that kind of capability.”

Nardecchia also details how AI accelerates onboarding, productivity, and recurring revenue growth while supporting critical infrastructure customers worldwide. Watch the full video below for more insights, and be sure to subscribe to the monthly Center Stage newsletter by clicking here.

On prioritizing the company strategy: It’s a tough thing to decide how to allocate your time. The approach I took when I first joined Rockwell about seven years ago was to over index on the transformation of the company perspective to help grow and scale, while simultaneously transforming the IT organization and righting the ship. So I emphasize trying to link what we’re doing in IT to the company strategy. I index what helps us achieve objectives, and then make sure we’re not just enabling the company strategy, but we’re integrated into it. And when you do that, you’re inherently improving your own IT operations. So I remain focused on the bigger picture, and then the IT stuff follows because it has to support the broader company strategy.

On industrial cybersecurity risks: In the manufacturing environment, everything’s about availability. Data integrity is important, but not as critical as availability. So IT shops will traditionally say they’re running things at two or three nines, so if the email goes out for a little while, it’s frustrating, but it’s not mission critical. In manufacturing, though, it’s mission critical. The industries I came from in either nuclear, chemical, or pharmaceutical, you’re either throwing away batches that cost millions of dollars or doing something that would create a safety event. In a manufacturing environment, that availability becomes the paramount thing. You have to keep things up and operational, and you can’t afford downtime. So you’re really running four or five nines all the time in manufacturing.

On how AI will impact cyber resilience: Resiliency is about redundancies across anything that could fail in both power and, in our case, controllers, right down to the IO level. You find your single points of failure and then build redundancy and automatic failovers between them so not any single thing can take you down. That’s how you have to think about it. And then even though you build in all these redundancies, you have to plan for the worst case scenario. Then you start thinking about recovery. The way I look 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 can you recover all your critical assets quickly. Do you have good backups, have you tested them, and can you recover within your recovery time and recovery point objectives so you can bring things back up. We focus on what are tier one or tier zero critical infrastructure and applications that have to run, and can they be brought back to a state where they were before. So it’s having immutable backups that couldn’t be violated or adulterated. We worry about that not only for ourselves, but for our customers, so our internal operations need to be tight.

On leveraging AI, machine learning, and predictive analytics: AI is a great topic for us. It’s embedded in every part of our strategy, go-to market, and products and services. But we’re a manufacturer, so we also use it in our manufacturing and at the enterprise level for typical productivity enhancements. One of the most interesting use cases for us was something we actually won a CIO Award for, which is our factory AI solution in a manufacturing facility in Singapore. It helps with optimization of production lines, builds quality, and helps with onboarding new engineers and production employees. It also helps embed assistance as something’s happening in the manufacturing environment, and guides operators through the recovery process and what’s happening in the process itself. It would typically take maybe six months to get a production employee in our assembly lines up to speed. And there’s sometimes a high turnover rate there or you get big demand, and as a result, you have to onboard more people. So we’ve been able to bring onboarding down to a few weeks by using AI assistance to guide them through the process and then combine that with AR and VR to give them visuals on how to do the assembly.