For decades, enterprises have thought about their data centers in terms of workloads. Applications came in, resources were provisioned, and IT leaders focused on making those workloads run as efficiently as possible.
AI changes that equation. Training and inference aren’t just workloads, they’re production pipelines. They consume vast amounts of data, create unpredictable demands on infrastructure, and require coordination across compute, networking, and security. The challenge is compounded by data that’s distributed across many sources—on-premises and in the cloud—and by the cost of managing it all.
To make AI real, the data center itself must evolve from supporting workloads to running factories: modular, repeatable, and secure environments designed to turn data into intelligence.
Why factories, not workloads?
The “factory” model isn’t just a metaphor. Like industrial factories, AI infrastructure needs:
- Standardized units that can be replicated and scaled, whether for inference at the edge or training in the core
- Lifecycle management that ensures each part of the production line operates consistently across hybrid and multicloud environments
- Tightly integrated systems where compute, networking, and security move in lockstep
This is the foundation of what we at Cisco call the AI-ready data center—infrastructure built for tomorrow’s intelligence, not yesterday’s workloads.
The Cisco approach
On any factory floor, the value isn’t a single machine. It’s in how every piece works together to create consistent outcomes. AI infrastructure is no different. Compute and graphics processing units (GPUs) act as the engines, the network becomes the conveyor system, and security provides the guardrails.
The Cisco Secure AI Factory with NVIDIA brings these components together with software and acceleration stacks into a validated, end-to-end stack. At the heart of the factory are Cisco AI PODs: modular, repeatable units that enterprises can scale up, replicate, or place wherever data is created and decisions need to be made.
AI PODs give you what you need today without boxing you out of where you need to go tomorrow. That flexibility saves money, reduces risk, and ensures your AI investments keep delivering value as your needs grow.
We’ve done the testing and validation up front so you don’t have to figure it out on your own. Everything works together.
Unlike other AI factories, ours is designed with security built in from the start. Every piece of data your AI creates is protected and you get clear visibility into how it runs. You can easily track, manage, and improve your AI over time.
This isn’t just about servers, switches, or software in isolation. It’s about an integrated production environment designed to help enterprises move fast with confidence, simplify operations at scale, and protect the investments they make in AI—today and tomorrow.
Inside the factory
Since every customer is starting from a different point, we’ve built choice into the factory floor:
- For customers who want to start small and scale over time, our latest UCS X-Series with X-Fabric 2.0 delivers composable GPU acceleration, allowing central processing unit (CPU) and GPU resources to scale independently without forklift upgrades.
- For those building the largest factories, we’ve introduced the Cisco UCS C880A M8 Rack Server powered by NVIDIA HGX B300 SXM GPUs and Intel Xeon 6 processors with P-cores. With up to 11x higher inference throughput and 4x faster training compared to the prior generation, the UCS C880A M8 is more than raw specs. The combination of performance, embedded security, and upcoming Cisco Intersight lifecycle management make it a powerful, reliable foundation for training and serving foundation models at scale.
- And because the network is just as critical when it comes to AI, the new Cisco Nexus 9300 Series Smart Switches extend 800G AI networking onto the factory floor. That means GPU-to-GPU traffic flows without bottlenecks, and you’ll get the visibility and policy control you need with workload-aware telemetry.
The road ahead
Enterprises don’t need another workload-optimized server. They need a factory model for AI: scalable, secure, and simple to manage across the data center lifecycle.
That’s the shift Cisco is leading. We’re giving customers the foundation to move from pilot to production and to run AI not as isolated projects, but as an industrial-scale engine for competitive advantage.
See how we’re bringing the next generation of future-ready
