Industrial automation professionals and operations leaders looking to improve cybersecurity, modernize with AI, or optimize their factory operations will find actionable guidance in this discussion between Phil Seboa, Ed Fuentes, and their guest, Brandon Artz. Key points include blending IT and OT cybersecurity, building smarter factories with connected data, and future-proofing skills in automation. These topics help readers address industry challenges and remain competitive.
Bridging IT and OT Cybersecurity
Blending information technology (IT) and operational technology (OT) networks creates new risks, especially as factories become more connected. Brandon Artz points out that traditional gaps between IT and OT teams can leave businesses exposed. “Communication is really key to success,” he notes, drawing a parallel to conflict resolution: both groups often have valid concerns but struggle to speak the same technical language.
Money and communication remain the biggest obstacles to rolling out serious cybersecurity measures. “You can get a lot of people to understand something's a problem, but to get them to pay for it, it's much harder,” Artz explains, highlighting the challenge of moving from awareness to action. He also observes that organizations tend to wait until a security issue directly impacts production before prioritizing investment.
Practical steps, according to Artz, include establishing good internal policies and aligning with documented frameworks like ISA or NIST. He urges companies to take care of basics before paying for external audits—doing so stretches limited budgets and avoids paying outside parties just to identify obvious weaknesses. As he cautions, air-gapping OT networks is rarely a viable solution, since “air gap sounds good on paper until production goes down,” and it often breaks down in practice.
Smart Factories Begin With Data Visibility
A truly “smart” factory starts with comprehensive data and clear operational visibility. Artz emphasizes the importance of collecting, connecting, and contextualizing plant-floor data so leaders can make informed decisions quickly. “Getting operations the visibility they need so they can react quickly… that's it. It’s getting operations the visibility they need so they can react quickly,” he says, describing tools that provide a real-time “single pane of glass” view across lines, locations, or enterprise-wide.
Artz has seen first-hand how the most advanced sectors, like automotive manufacturing, achieve high efficiency by standardizing data collection, communication, and procedures. He recalls, “Automotive is the most razor thin margin efficient machine you've ever seen run, and it runs well”—a benchmark for other industries. For smaller manufacturers, he recommends following industry frameworks, performing diligent walkthroughs, and creating plant-wide standards. This method helps ensure data isn’t siloed and that new automation or AI initiatives are built on sound foundations.
Preparing for Automation’s Future: Skills and AI Integration
Technology in factories is moving rapidly, with trends like AI, machine learning, and in-house automation tools becoming mainstream. Artz encourages today’s professionals not to specialize too narrowly. “For you to succeed in the future, you're gonna have to know a little bit about a lot. You don’t have to be an expert,” he shares, noting the importance of curiosity, hands-on experimentation, and cross-disciplinary problem solving.
He reminds listeners that traditional, process-based industry knowledge is just as important as knowing the latest coding language or AI tool. “Bringing all that together and understanding what are his needs… that's what you have to do for these to be a successful venture.” As roles shift, documenting “tribal knowledge” and blending it with up-to-date AI systems and connected platforms will become even more important. Artz predicts, “We need to maintain that knowledge. If we lose that, it's going to be hard to get back.”
Key Quote From The Episode
“You can get a lot of people to understand something's a problem, but to get them to pay for it, it's much harder.” – Brandon Artz
Key Takeaways
00:09:35: Money and communication are the primary challenges in moving from cybersecurity awareness to effective action in industrial environments.
00:37:46: A smart factory requires real-time data visibility and operations dashboards so leaders can respond promptly to changing conditions.
00:24:38: Success in modern automation needs cross-disciplinary knowledge—combine traditional engineering with digital skills, and continuously learn as technology evolves.
Wrap Up
Industrial professionals must bridge IT and OT gaps for robust cybersecurity, focus on developing data visibility for smarter factories, and continually refresh skills to remain current as AI and other technologies advance. Companies should:
Establish regular, structured dialogues between IT and OT teams.
Prioritize step-by-step improvements based on standard frameworks, using in-house expertise and targeted external audits.
Invest in skills development and documentation of operational knowledge to protect business continuity as automation grows.
By following these steps, organizations can create safer, smarter, and more resilient manufacturing environments.
About the Guest
Brandon Artz is an industrial controls and cybersecurity professional known for his broad skillset and passion for practical solutions. With experience ranging from automotive to automated warehousing, he specializes in integrating IT/OT, process engineering, and emerging technologies to improve manufacturing efficiency and security. Artz combines industry experience with ongoing experimentation and a commitment to sharing knowledge. Connect with him on LinkedIn and Medium.
