AI in Manufacturing: How Artificial Intelligence Is Transforming European Industry

Artificial intelligence is moving beyond experimentation and into industrial production.

Across manufacturing, AI is being used to inspect products, analyse production data, optimise processes and support increasingly autonomous systems. For European manufacturers, the opportunity is not simply to adopt another digital technology. It is to use AI to tackle some of industry's most persistent challenges: quality, productivity, flexibility and competitiveness.

The shift is already visible on factory floors.

AI is changing how manufacturers manage quality

Quality control is one of the clearest applications of AI in manufacturing.

BMW Group, for example, has developed AIQX – Artificial Intelligence Quality Next, an AI-powered quality platform that analyses sensor and image data from production lines in real time. By detecting faults as they occur, the system can provide immediate feedback to employees, helping to improve product quality and reduce defects.

At BMW's Spartanburg plant in the United States, AIQX is also being used for visual and acoustic quality inspection. The manufacturer has established the technology as a standard and is now assessing options to make the system available to suppliers.

The example shows where industrial AI can create immediate value: not by replacing an entire production system, but by improving specific processes where large volumes of production data are already available.

From individual applications to AI-powered factories

Other manufacturers are taking the transformation further.

In Germany, Siemens announced an investment of around €200 million in March 2026 to build a new AI-based, digitalised and automated factory at its Amberg site.

Scheduled for completion by 2030, the facility will manufacture high-tech electronic products for Siemens Smart Infrastructure. Siemens plans to use industrial AI, digital twins and advanced automation to create a highly flexible production environment while responding to growing demand.

This points to a broader shift in smart manufacturing: AI is moving from individual use cases towards production environments where data, digital twins, automation and intelligent systems increasingly work together.

BMW's Virtual Factory offers another example. Digital twins have been developed for more than 30 of the company's production sites, allowing planners to simulate changes virtually before implementing them on the factory floor. BMW expects the technology to reduce production planning costs by up to 30%.

The next frontier is physical AI

The convergence of artificial intelligence and robotics could take this transformation a step further.

BMW is already testing humanoid robots as part of its Physical AI strategy. In June 2026, the manufacturer announced a new project involving Figure 03 humanoid robots at its Spartanburg plant, exploring how intelligent machines can be integrated into real production processes.

But successful AI adoption cannot start with the technology alone.

Manufacturers need reliable production data, connected equipment, robust cybersecurity and employees who understand both industrial processes and the digital tools supporting them. Europe is also expanding the infrastructure available to support AI development and adoption, with 19 AI Factories being established across the continent to connect computing power, data, research and industry.

For manufacturers, the most valuable AI project is therefore not necessarily the most sophisticated. It may be the one that reduces scrap, detects a defect earlier, prevents downtime or makes a production line more flexible.

The key question is shifting from “How can we use AI?” to “Which industrial problem should AI help us solve?”

That is where artificial intelligence can move beyond the technology trend — and start delivering measurable industrial performance.

Looking for the technologies shaping the next generation of manufacturing? Discover the companies exhibiting at Global Industrie 2027.