In Part 1 of this series, I discussed the rise of industrial intelligence, where AI, advanced processing, and high-performance connectivity are converging to transform industrial operations. This new era is characterized by increased automation, AI-driven decision-making, and mobility-focused use cases—from connected workers to self-guided industrial vehicles.
I also shared a key insight: legacy infrastructure wasn’t designed for a world increasingly shaped by AI at the edge, and businesses are now grappling with the resulting gaps in coverage, reliability, latency, and security. As we move closer to physical AI and more intelligent, autonomous systems and devices, these challenges will only intensify.
What’s needed now is a new approach—a network architecture developed for industrial AI. At Celona, this architecture is centered on a concept we call the new wireless edge.
The Industrial AI Stack
The new wireless edge isn’t just an evolution of networking. It represents a fundamental shift in how compute and connectivity are integrated to enable real-time intelligence at the edge. It’s structured around the requirements of the Industrial AI Stack—a framework that defines how these capabilities must interact. At its core, the stack consists of three critical layers:
- Device layer: This includes AI-enabled machines, sensors, robots, and industrial handhelds, many of which now feature on-device AI models for local inference and decision-making. These devices serve as the first point of data creation and action.
- Connectivity layer: This is the wireless fabric that links the devices to the edge cloud. It must deliver ultra-reliable, low-latency connectivity with deterministic performance, allowing data to move in real-time without delay or disruption.
- Edge cloud layer: This is where more complex AI workloads are processed. It brings centralized computing power closer to where data is generated, supporting real-time automation and control while maintaining scalability and security.
The ability to move data seamlessly between these layers—especially from on-device AI to the edge cloud—is essential. Without robust connectivity, data becomes siloed, latency increases, and the promise of industrial intelligence is compromised.
Another critical element is security. The Industrial AI Stack must be designed with built-in safeguards across all three layers—including authentication and access controls, encrypted communications, and a zero-trust approach—to ensure system integrity and data protection.
Why Private 5G Is Foundational
Meeting these performance and security demands requires private 5G.
Unlike legacy infrastructure, private 5G was built for dynamic industrial settings. It extends coverage across large facilities, through metal-dense structures, and to mobile devices and equipment—whether it’s a facilities engineer with a connected tablet or an autonomous vehicle navigating a warehouse. Notably, it does all this using significantly fewer access points.
Private 5G also provides the reliability necessary for automation and real-time decision making, where network uptime is crucial. And with SIM-based authentication and end-to-end encryption, it delivers enterprise-grade security to defend against ever-increasing cyber threats.
Together, these capabilities create a unified wireless fabric that powers real-time inference, supports a growing array of connected devices, and helps scale AI across the enterprise as new use cases and capabilities emerge.
From Connected to Intelligent Operations
With the new wireless edge in place, industrial organizations can unlock the full value of industrial intelligence. It begins with equipping frontline workers with real-time access to GenAI copilots, AR-assisted workflows, and hands-free data capture. Soon, these workers will be able to interact directly with intelligent machines, querying them about their health, performance, or predictive maintenance status.
Across operations, private 5G becomes a strategic enabler, accelerating automation, machine-to-machine collaboration, and real-time analytics without compromising control or reliability.
This is more than just a network upgrade. It’s what powers the next generation of adaptive, AI-powered operations.
The Path Forward
As industrial intelligence redefines the requirements of enterprise networks, the decisions made today will determine how effectively organizations can compete tomorrow.
If you’re a CIO or IT leader, now is the time to ask the tough questions. Do you have the visibility and control you need at the edge? Can your current network support real-time AI applications and tools for frontline workers? Are you building a foundation that can scale with your AI ambitions?
Companies that take action now and invest in a wireless edge powered by private 5G will be well positioned to lead in this new era of industrial transformation.
In Part 3 of this series, we’ll explore how industrial organizations are deploying this architecture, and the impact it’s having across automation, productivity, and innovation.
