Picture this: You’re deep in the heart of a bustling food processing plant, where every second counts, and precision is everything. The hum of machines surrounds you, but something far more intelligent is at work.
AI is your silent, all-seeing ally, ensuring that every ingredient, every process, every movement is flawless. You’re prepping a batch of white powder for a major food product—seems routine, right? But hidden within that powder, there’s a potential contaminant, something invisible to the naked eye.
Cue AI-driven machine vision. In a flash, multi-spectral sensors kick in, scanning every inch of that batch with laser-like precision. An image is instantly generated—a composite masterpiece that highlights the problem. The system locks in on the contaminant, and within moments, it’s identified, rejected, and quarantined.
But the action doesn’t stop there. Behind the scenes, AI is analyzing real-time operational data like a detective solving a case. It traces the issue back through the supply chain, uncovering a potential glitch in ingredient sourcing. Instantly, connected workers are armed with insights, actionable data in their hands, ready to make immediate corrections. No delays. No guessing games.
Need new ingredients? Done. Automated warehouse robots zip across the floor, delivering replacements to the line. Everything flows seamlessly, like clockwork.
And it’s all captured—every decision, every adjustment—digitally recorded for governance. Compliance? Check. Meanwhile, the system updates operational procedures, feeds them into virtual reality training modules, and provides real-time augmented reality work instructions, ensuring that this kind of problem doesn’t happen again.
This isn’t just automation. This is AI transforming the way you work, empowering your team to catch issues early, solve them faster, and protect the brand at every step. In this world, you’re in control, with AI as your sharpest tool, ready to keep the production line—and your business—running smoothly.
Driving positive business outcomes
The scenario above is just one example of how AI can drive positive business outcomes in industrial settings. Some of the technology’s greatest value comes through empowering workforces with better real-time decision-making, actionable operational insights, increased situational awareness for predictive maintenance and safety, and enterprise-wide intelligence for sustainability programs.
As Industry 4.0 continues to develop, industries must look for opportunities to go beyond just “doing things better” and augment that with a culture which evaluates and implements ways of “doing things differently.” Core to this are actionable insights from manufacturing data, collected through Internet of Things (IoT) sensors and automation systems.
Consider an AI tool that continuously monitors and analyzes industrial equipment, processing data to detect patterns that could predict a potential gas leak or chemical spill. AI can generate relevant action steps for crisis situations, helping managers take the most appropriate action, often without having to disrupt production or put anyone in danger.
Similarly, AI can track and analyze the biometric data of a lone worker operating heavy machinery, like a crane or underground mining vehicle, to judge whether that person is showing signs of fatigue. And from a sustainability perspective, AI can be leveraged to trace a company’s product’s components through every stage of the supply chain, even validating the findings with a digital product passport or blockchain technology.
Further accelerating enterprise digitalization is the rise of generative AI, whose natural language processing capabilities enable more intuitive human-machine interactions and improve efficiency in complex industrial environments. For instance, Nokia’s MX Workmate solution leverages GenAI to give workers contextual, language-based insights in areas such as enhanced predictive maintenance, streamlined decision making, and safety scenarios.
Building the foundation for transformative change
If you don’t have an eye on these kinds of things but your competitors do, that puts you at a disadvantage.
According to a 2024 report by the International Monetary Fund, “artificial intelligence is set to profoundly change the global economy, with some commentators seeing it as akin to a new industrial revolution.” Already, about 60 percent of jobs in advanced economies are exposed to AI, with many positioned to “benefit from enhanced productivity through AI integration.” In addition, Deloitte predicts nearly 2 million jobs in U.S. manufacturing could be left unfilled by 2033, with investments in technology “pivotal to how manufacturers position themselves for success.”
As the above use cases illustrate, human-AI integration is not something to be feared but something to be desired. In fact, it’s quickly becoming the new table stakes.
At Nokia, we believe that a unified, ecosystem-neutral, industrial edge platform—one that integrates AI, computing, applications, and wireless networking—is key to a company’s enterprise digitalization efforts. Such a platform enables simple-to-use, scalable solutions for industrial businesses to capture, process, analyze, and act on real-time operational technology (OT) data at the edge of the network, close to the source of IoT and automation data generation. This leads to completely situational and contextually aware industrial sites that empower workers for enhanced real-time decision making while ensuring better data security, sovereignty, robustness, resiliency and latency.
Collaboration is essential for real-world digitalization solutions, and that’s where companies like Nokia can help. When choosing a partner, look for expertise in connectivity, industrial devices, AI analysis and edge platform technology—with the goal of seamlessly integrating data and applications from multiple sources without the need to reprogram or replace industrial controllers and other critical equipment.
Every industrial business is at a unique stage in their AI journey, but finding the right partner will be key to both ongoing optimization and long-term transformation.