Is private 5G the key to scaling AI in manufacturing

Modern manufacturing floors today hum with the sound of machinery monitored by increasingly sophisticated intelligence systems. Machine learning algorithms predict when equipment will fail before breakdowns occur. Computer vision systems catch defects that human eyes might miss. Production optimization models adjust schedules in real time based on supply chain fluctuations. 

Despite these advances, most manufacturers know they're only scratching the surface of what artificial intelligence can accomplish. The bottleneck isn't the sophistication of AI algorithms—it's the network infrastructure needed to support them at scale. 

 

Industrial AI’s data hunger 

AI in manufacturing consumes massive volumes of data, and not just any data. These systems need the right information, captured at the right moment, and delivered with perfect timing. A steel plant running predictive maintenance algorithms might generate terabytes of sensor data daily while an automotive assembly line using computer vision for quality control processes millions of images every shift. This requires a network, like Private 5G, that can deliver the speed, capacity, and low latency needed to transport this data without bottlenecks.  

Two paths for manufacturing intelligence 

According to the 2025 Manufacturing Momentum Report, 43 percent of manufacturers have now identified specific AI applications for their operations.¹ These applications generally follow two distinct paths, each with unique connectivity demands.  

• Digitalization: AI-driven insights from connecting sensors, devices, and systems to gather more granular operational data, enhancing process optimization, quality management, and supply chain efficiency.

• Real-time automation: AI must instantly detect and act where split-second decisions and ultra-low latency are non-negotiable. When a computer vision system detects a defect on an assembly line, it must instantly communicate with control systems to remove the faulty product.  

Traditional networking approaches struggle with both scenarios. Wi-Fi networks can become overwhelmed by the data volumes that digitization AI requires, while their latency and reliability limitations make real-time automation applications impractical in many environments. Private 5G’s reliability and performance make both digitalization and real-time control possible at scale.  

 

Contextual intelligence across operations 

One of the most compelling aspects of AI in modern manufacturing is its ability to understand and deliver contextual intelligence—tailoring insights based on who, what, where, and when of each situation.  

A quality control manager reviewing production batch data needs high level trend analysis and exceptions. Meanwhile, a line operator on the floor requires real-time alerts and clear corrective action. Manufacturing AI provides the same data but with customized insights—delivered in the right way, to the right person at the right moment.  

This contextual intelligence becomes especially critical during shift changes. Subtle warning signs, like a machine vibrating more than normal, a gradual temperature drift, or an emerging pattern of defects, can be easily missed by incoming workers unfamiliar with the evolving situation. Additionally, seasoned operators often rely on instincts built from experiences, but these subtleties may be missed in traditional handoff procedures. AI systems, powered by real-time data and private 5G connectivity, can detect and communicate these nuances—making every shift smarter, safer and more informed.  

Why private 5G is the missing piece within industrial environments  

Manufacturing facilities pose unique—and often extreme—networking challenges that conventional connectivity simply can’t handle. For example, chemical plants operate in potentially explosive atmospheres where traditional wireless equipment presents safety risks and often isn’t certified for use. Steel mills generate intense electromagnetic interference that can disrupt standard communication protocols, causing dropped signals and unreliable data transfer. Wiring every sensor, camera and machine with fiber optic cables in these harsh or sprawling environments can cost tens of thousands of dollars per connection point. The economics become particularly problematic when facilities need to adapt quickly to changing production requirements. 

Private 5G networks offer a smarter, more scalable solution. With just a few strategically placed cellular access points, private 5G can deliver secure, high-performance connectivity across entire facilities—covering thousands of devices without the expense, complexity, or rigidity of fiber or legacy wireless systems.  

Additionally, unlike Wi-Fi and other wireless solutions, private 5G provides guaranteed performance for mission-critical applications. These networks can prioritize traffic intelligently, ensuring safety-critical AI systems always have the bandwidth and low latency they need, even when handling massive data flows from other applications. 

 

Real-time intelligence in action 

The true power of combining private 5G with manufacturing AI emerges in applications requiring immediate action. Consider a pharmaceutical manufacturing line where AI systems monitor product quality at multiple checkpoints. When contamination is detected, the system must instantly isolate affected products, adjust process parameters, and alert quality control personnel. 

This scenario requires seamless coordination between computer vision systems, process control equipment, database systems, and human operators. Without reliable, low-latency connectivity, even sophisticated AI algorithms can't implement decisions quickly enough to prevent quality issues or production disruptions. 

Meeting manufacturing's unique AI requirements 

While AI is transforming industries across the board, its application in manufacturing is fundamentally different for enterprise use cases. AI can't afford to deliver uncertain recommendations. Product lines can’t risk experimenting with AI recommendations that might lead to costly errors. Safety systems must respond reliably every time. Quality control applications must catch every defect without generating excessive false positives. 

These requirements shape how manufacturers deploy AI. Unlike cloud-based consumer AI models that rely on broad, variable data sources, industrial AI requires strict control over data inputs to eliminate the risk of contamination or bias. A flawed algorithm isn’t just an inconvenience here, it could mean defective products, supply chain disruptions or compromised worker safety.  

Because of this, manufacturers must invest heavily in AI solutions tailored to their specific processes and assets, trained on data from their own production environments.  

The connected AI-powered enterprise

Forward-thinking manufacturers are already moving beyond facility-level optimization to create truly connected enterprises where AI systems span entire value chains. This approach integrates customer demand forecasting, supply chain management, production planning, quality control, and distribution logistics into unified intelligent systems. 

Private 5G makes this possible with secure, scalable connectivity, enabling work across all business functions. Whether AI systems are analyzing production equipment in facilities, monitoring transportation assets in transit, or tracking products at customer locations, they can operate on the same network infrastructure with the same performance guarantees. 

This transformation represents more than incremental improvement—it's a fundamental shift in how production operations function. The question for most manufacturers isn't whether this transformation will happen, but how quickly they can adapt to take advantage of the opportunities it creates. Organizations that move decisively to build the right foundation will be positioned to lead their industries for true Industry 4.0 digitalization.  

 

Ready to transform manufacturing operations with private 5G? 

Explore these resources to see how industry leaders are already implementing intelligent manufacturing solutions: 

• Advancing 5G computer vision with Hitachi, AWS 

• Smart Factory inspections with private 5G 

• First Mobile Campus network in Greece for smart manufacturing 

• Machine learning forecasting: Why, what and how 

• Inside Ericsson's Cutting-Edge 5G Manufacturing Hub in the US 
  

1.  “The 2025 Manufacturing Momentum Report”, The Manufacturer, March 2025.