A few weeks ago, I wrote about the gap between AI ambition on the factory floor and the industrial network infrastructure reality. The response confirmed what many of you already know firsthand: the network is where industrial transformation either gains traction or quietly stalls. What I didn't fully address is the question that came back most often — not whether to modernize the network, but how to do it right. That's the conversation worth having now.
Software-defined industrial automation is reshaping manufacturing economics
The shift is structural, not incremental. AI-powered machine vision is replacing rules-based inspection. Virtual PLCs, HMIs, and industrial PCs are migrating off dedicated hardware onto hyper-converged compute environments. Digital twins are consuming continuous data feeds from hundreds of endpoints simultaneously.
Audi's Edge Cloud for Production initiative shows what this looks like at scale. By virtualizing core production control assets, Audi created an infrastructure that is faster to update, easier to secure, cheaper to deploy and maintain, and ready for the next wave of AI capabilities — without hardware procurement cycles or physical intervention across dozens of machines.
The opportunity is real. According to Cisco's 2026 State of Industrial AI Report, 61% of industrial organizations are actively deploying AI in their industrial environment. But 97% acknowledge that AI workloads exceed the performance and reliability assumptions of traditional industrial networks. The network is the foundation on which software-defined manufacturing and industrial AI either stand or collapse. Here is what getting it right requires.
Scalable performance: built for AI-driven data demands
Machine vision cameras generate continuous high-resolution video streams. Virtual PLCs require predictable latency where millisecond disruptions can halt production. Digital twins demand high-bandwidth connectivity from sensor to cloud, without impacting existing control traffic.
Having 10Gbps network connectivity on the plant floor is not luxury anymore. But more than throughput, a modern industrial network must offer Quality of Service features such as frame preemption to ensure AI traffic can coexist with time-sensitive control protocols. Power over Ethernet delivering up to 90 watts per port can now power a new generation of cameras, sensors, and edge compute nodes, helping both reducing the hidden costs of a separate power infrastructure and simplifying deployment.
Software-defined networking capabilities allow IT and OT teams to stretch industrial VLANs across routed fabrics, dynamically connecting new AI applications to brownfield assets with low-latency, loss-less resiliency — critical when virtual PLCs and HMIs depend on the same deterministic communications they had when running on local hardware.
Wireless connectivity is equally critical to enabling AI at scale. Autonomous guided vehicles, mobile robots, and remotely operated equipment cannot be tethered — and the wireless networks supporting them cannot afford to drop a packet at the wrong moment. This requires wireless technology purpose-built for industrial environments: zero-delay handoffs as vehicles move between coverage zones, ultra-low latency for real-time control loops, and high throughput to stream the video feeds that autonomous operations and remote control depend on.
This is what makes software-defined manufacturing viable plant-wide beyond the pilot cell.
Security fused into the network
With more software-defined industrial controls and AI applications, industrial data moves across OT, IT, and cloud domains, and the attack surface expands. The traditional response — deploying a dedicated appliance for every security function — breaks down at scale. It is cost-prohibitive, operationally burdensome, and leaves gaps that threats will find. The better answer is to make the network itself the security infrastructure.
Deep packet inspection embedded in switches and routers extracts full asset inventory, communication patterns, and vulnerability data at the network edge — without duplicating traffic or adding hardware. Because discovery happens within the network equipment, it reaches assets behind NAT boundaries that block centralized solutions, closing the visibility gap that leaves up to 80% of OT devices unseen in conventional deployments.
Isolating production cells using network segmentation is key to limit the blast radius of an attack. Segmentation policies can be enforced by switches to simplify deployment at scale. With full visibility on OT assets, software tools can automatically group assets and suggest zones and conduits aligned to ISA/IEC-62443 standards. OT teams retain operational control without depending on IT for every move, add, and change. Simulation ensures policies will not disrupt production. When policies are pushed to industrial switches, the network becomes your defender.
Zero-trust remote access gateways embedded in switches and routers throughout the network means every asset is reachable — regardless of its IP address or NAT configuration. There is no dedicated hardware to deploy and no complex firewall rules to maintain, reducing costs and eliminating risks from bad credential hygiene.
A modern industrial network can be sensor, enforcer, and gateway — simultaneously — to give you the security foundation you can trust to deploy software-driven industrial control and industrial AI workloads.
Operational simplicity: intelligence where it's needed most
As industrial networks become more sophisticated, simplicity becomes an imperative to help maintain uptime. OT teams understand the physics of manufacturing and the logic of industrial control systems, but when a network issue strikes during production, they don’t have time to escalate to a networking expert and must solve it themselves.
Imagine a modern industrial network with AI-powered troubleshooting features capable of detecting network issues, performing root-cause analysis automatically, and pushing actionable remediation steps directly to whoever is closest to the problem — in plain language, using the asset names the OT team already knows. This is available now.
We are entering an era where AI can act as that digital coworker. The goal is not to replace human expertise. It is to amplify it — shifting the burden of diagnosis from people to the system, so your team spends less time firefighting and more time keeping production moving. Operational simplicity doesn't mean removing complexity from the network. It means ensuring that complexity never becomes a barrier to uptime.
The decision in front of you
Scalable performance, embedded security, and operational simplicity are the three load-bearing requirements of any industrial network built for the software-driven factory and industrial AI. Miss one, and the others cannot compensate.
Cisco brings more than two decades of industrial networking experience, a validated reference architecture tested against real industrial control systems, and an end-to-end portfolio engineered for these demands — from ruggedized switches with 10Gbps connectivity and 90W PoE, to ultra-reliable wireless with low latency and seamless roaming, to security embedded directly in network hardware, to agentic AI troubleshooting that empowers OT teams to resolve issues without escalation. Explore modern industrial networking here.
The manufacturers who will lead the next decade are building on infrastructure designed to sustain, scale, and secure transformation over time. The factory floor is ready. Make sure the network supporting it is, too.
