“About ten years ago, the buzzword ‘Industry 4.0’—referring to digitized production—was introduced at the Hannover Messe. Expectations were enormous, though not all of them were met. Currently, artificial intelligence is electrifying the world’s leading industrial trade fair: both industry associations and companies are emphasizing how seriously they take the subject, noting that they are already using AI and that it could become a major competitive advantage. The vision is that of a self-controlling AI factory. The question remains, however, as to what things will actually look like inside those factory walls. Four experts outline their expectations.
Humans in a leading role
Martin Ruskowski is Head of the Innovative Factory Systems research department at the German Research Center for Artificial Intelligence (DFKI) in Kaiserslautern and Chairman of the Board of the Smart Factory there—an initiative that views itself as a model for the factory of the future:
‘What is an AI factory? Let me start with what it is *not*. Erase from your mind the clichéd image of humanoid robots performing monotonous movements in a vast, empty hall. Humans will continue to play a crucial role in modern production facilities—and I mean "crucial" quite literally: they are evolving from an executing role into a leading one.
The way they interact with machines is changing fundamentally: using chatbots, they can issue commands in natural language and, in return, receive information and recommendations from machines capable of independently detecting, assessing, and even rectifying errors. Ultimately, the human makes the final decision, but the knowledge base informing that decision is far superior to what it used to be—thanks to the well-processed data available in such a factory.
That data forms the foundation for the use of AI.
However, not everything that defines an automated or even autonomous factory is necessarily AI. The foundation consists of classical automation and the digitization of equipment, the collection, standardization, and sharing of data, and the interconnection of components.’”
I can layer AI onto this basic framework in the form of self-organizing systems that control themselves via AI agents; instead of being rigidly programmed, they respond flexibly and resiliently to problems. They can execute production steps independently and adjust the sequence as needed. Humans no longer need to anticipate every eventuality and program it into the machine.
Our Open Smart Factory Architecture demonstrates how this works; it describes the interconnection of IT and OT, intelligent software agents, and standardized data formats. It turns the smart factory into reality. The benefits are obvious: AI can accelerate production while making it more profitable and sustainable. Changes to production or the introduction of new products can be implemented much faster; "batch size one" production becomes economically viable; and we can leverage marketplaces and engage in shared production. We achieve higher equipment utilization, implement predictive maintenance, save materials, and reduce waste. The core business model here is driving increased efficiency and productivity.
In my view, the perfect AI factory does not yet exist in Germany. There are some large SMEs that have made significant progress and are implementing individual pieces of the puzzle. We are seeing an increase in inquiries, too, and hopefully, we will soon be able to roll out our architecture for widespread use. The key point is that this transition won't happen overnight; it must take place step by step. However, it is essential for German companies to catch up, as China and the USA threaten to overtake us. The new concepts are ready and must be implemented now if Germany is to remain economically competitive as a manufacturing hub."
Redefining Automation
Matthias Großmann heads the Product Line Digital Products division at Festo, an automation company based in Baden-Württemberg:
"The AI factory of the future combines autonomous, data-driven systems with networked automation. The goal is flexible, efficient, and sustainable production that adapts quickly to demand, product variety, and disruptions. The focus is on the interaction between humans and machines—for example, through humanoid robots that are redefining existing approaches to industrial automation.
The human element remains, but AI can relieve workers of highly repetitive tasks. This requires all critical components to be digitally connected and the resulting data—transformed into actionable information—to be fully integrated into business processes. Festo offers solutions such as predictive maintenance, enabling automated decision-making and flexible responses to changing conditions, whether in controlling material flow, detecting wear for maintenance purposes, or performing quality inspections. We also monitor machine conditions using sensors and intelligent analysis to ensure maintenance is scheduled in a timely manner and downtime is avoided.
In the future, AI will not only help digitize existing processes and make them more efficient; it will also enable us to rethink and redesign processes from the ground up. To fully realize this potential, these capabilities must be factored in right from the initial design stage of new systems. AI is not limited to the operational phase of manufacturing companies; it also supports the planning of new production facilities. Using digital twins, new systems can be virtually simulated and commissioned, saving valuable time and minimizing risk. For instance, employees can familiarize themselves with the new environment in a virtual space. At Hannover Messe, Festo is showcasing the first valve terminal with integrated AI."
Unprecedented Performance
Thomas Fechner is a member of the Executive Board of Bosch Rexroth AG and is responsible for the Factory Automation business unit:
"AI is increasingly being deployed in factories, making them more high-performing than ever before. Until now, it has been the job of experts and suppliers to gather vast amounts of parameter data and improve production workflows by adjusting programs in expert systems to keep factories up to date. This process is time-consuming, complex, and laborious. AI can significantly accelerate these program adjustments.
This is because AI offers impressive capabilities for handling parameter data and program code.
However, to do this, AI requires broad and deep integration with a factory's technical systems—much like the nervous system our bodies use to perceive and control our movements."
In concrete terms, this means we must consolidate the data streams—currently still largely separate—and access to industrial control systems (extending deep into the machinery itself) into a single "data highway." This highway must span everything from production lines and robot fleets to overarching factory control systems. Within such an integrated network, AI agents can operate at various levels of granularity, optimizing factory operations in real time.
The key to success lies in secure and flexible access to the control systems governing factory operations. Merely accessing machine data—as is standard in Industry 4.0—is no longer sufficient. Consequently, the speed and effectiveness with which AI’s potential is realized depend on how quickly comprehensive factory control systems are established. The necessary technology has been available for years and proven in practice.
What does this mean for the human workforce? People will remain crucial. While AI generates powerful analyses and recommends optimizations, human expertise is still required to oversee operations and orchestrate adjustments. At the same time, operating even the most complex factory technology is becoming increasingly simple.
We can already use AI to communicate with machines in everyday language and adjust processes without needing to master complicated control terminals or programming languages.
This development presents a major opportunity for Germany as an industrial hub, as AI-based factory automation solutions strengthen the competitiveness of German industrial manufacturing in the global market.
Geopolitical Strengthening
Hartmut Rauen is Deputy Executive Director of the VDMA (Mechanical Engineering Industry Association):
"An AI-driven factory is dominated by networked machines, robots (including humanoid ones), and 'intelligent' systems. Together, they autonomously plan, execute, and optimize production steps and other processes. The foundation of such factories is the integration of digital and data-driven solutions as a core component of the company and its value creation." It is equally important that AI be deployed as a key efficiency technology across all areas—whether in administrative functions or in the form of "embodied AI" within machinery and plant systems. Humans then primarily assume supervisory, control, and strategic roles, intervening in complex situations and focusing more on innovation.
AI-driven factories operate based on a different mindset than conventional factories: processes are not automated according to fixed, one-time rules but are instead data-driven and autonomously optimized using AI methods. While traditional factories often require rigid workflows and manual intervention, AI-driven factories allow for the dynamic adjustment of production schedules, workflows, and parameters. Errors and deviations are detected early and automatically corrected thanks to the continuous collection and analysis of data.
Consequently, production can handle small batches and individual customer requirements in significantly less time.
Take time into account. In addition, machines and systems can communicate with each other automatically and make independent decisions.
The use of AI in manufacturing companies is already accelerating the development of products, as we know from VDMA surveys. Among other things, through AI-based simulations and support in software development, which makes products ready for the market more quickly. Self-learning systems in production can increase production efficiency by optimizing workflows and reducing waste. Predictive maintenance prevents failures and extends machine life, which also saves costs. This creates significant time and cost savings as well as new business models.
AI factories are the next evolutionary stage of Industry 4.0. They rely on intelligent systems and a holistic view (even across company boundaries) instead of purely automated processes. The Industry 4.0 approach forms the basis for digitalization and networking, while AI as a key technology makes self-optimization, autonomy and flexibility of factories possible. AI factories in Europe would strengthen the entire economic area and thus also Germany economically and geopolitically. The ability to react quickly to market requirements while keeping costs low provides clear advantages in international competition. However, it is important that AI factories are not viewed on their own, but also the (data) ecosystem around them. Initiatives such as Manufacturing-X [1] offer the opportunity to confidently share data along the value chain and thus provide the AI models with further nutrients for additional efficiency and knowledge gains." [2]
1. Manufacturing-X Germany is a government-backed strategic initiative aimed at creating an open, sovereign, and interoperable digital data ecosystem for the industrial sector. Supported by the Federal Ministry for Economic Affairs and Climate Action (BMWK) with €140 million in funding, it builds upon Industrie 4.0 principles by allowing companies to share production and supply chain data while strictly maintaining data sovereignty.
The initiative addresses the critical need for supply chain resilience, sustainability, and global competitiveness by establishing secure digital networks. Instead of a single centralized platform, it enables federated "data spaces" where sensitive corporate and proprietary information remains protected.
Key industry-specific projects under the Manufacturing-X umbrella include:
• Catena-X: A pioneer data ecosystem designed for the automotive industry.
• Factory-X: A lighthouse project explicitly designed for mechanical and plant engineering.
• Chem-X & Semiconductor-X: Tailored data spaces targeting the chemical and semiconductor industries, respectively.
Strategic oversight for the initiative is provided by the Manufacturing-X Council Germany (MXCG), which coordinates national projects and aligns them with international standards. Because value networks are inherently global, the German initiative works closely with the International Manufacturing-X Council (IMXC) alongside partner nations like Austria, Japan, South Korea, and the United States.
2. Was kann eine KI-Fabrik? Frankfurter Allgemeine Zeitung; Frankfurt. 22 Apr 2026: 20. Von Uwe Marx, Frankfurt
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