A new era is dawning in intralogistics. Just a few years ago, robots performed repetitive tasks that had been programmed by humans. Today, machines learn, respond to their environment, interact with people, and make decisions independently. “We are currently experiencing the ChatGPT moment for robotics,” says Prof. Dr. Katharina Hölzle, director of the Institute for Human Factors and Technology Management (IAT) at the University of Stuttgart and managing director of the Fraunhofer Institute for Industrial Engineering (IAO). Just as artificial intelligence (AI) has opened up new dimensions in text and image generation within a very short time, it is now enabling robots to grow far beyond rigid routines. Physical AI, the combination of robotics and adaptive algorithms, turns tools into partners for humans that work flexibly, proactively, and context-sensitively.
This technological dynamic is impacting an industry under pressure. While international competitors are rapidly investing in AI-supported robotics and thus in a successful economic future, companies in Germany are struggling in a challenging economic situation. This reduces the scope for wrong decisions, leading to caution when introducing new technologies. But this is precisely where a historic opportunity lies: Those who exploit the potential of intelligent robotics now can not only make processes more efficient and resilient, but also position themselves as pioneers in the global market – and take Germany to a new level as a production location.
Intralogistics and AI robotics: the status quo
Intralogistics is considered the silent force behind functioning supply chains. It is highly relevant, but rarely in the spotlight. The industry is currently facing growing challenges. Although production volume in Germany grew by three percent to €27.7 billion in 2024 and Germany exported goods worth €20.8 billion, China is pulling ahead in international competition with €26.8 billion in exports (+13%).
There is also a gap between aspiration and reality when it comes to the use of AI. Although more than half of logistics companies are convinced that AI will be crucial to success in the future, only 12 percent are currently using AI productively, while the vast majority remain in pilot or test phases. The biggest obstacles are: high implementation costs (41% of companies cite this as the main obstacle), data protection and IT security concerns (36%), and a lack of technical expertise (35%). Added to this are questions of acceptance when dealing with autonomous systems.
Nevertheless, Germany has a strong starting position: With 429 industrial robots installed per 10,000 employees, robot density is above the European average, albeit significantly behind the frontrunners South Korea (1,012) and Singapore (770). Around one-fifth of German industrial companies already use AI robotics, with a further 42 percent planning to introduce it.
Physical AI as a game changer
It is becoming increasingly clear that the combination of AI and robotics marks a turning point for intralogistics. While classic automation follows fixed programmed processes, machines with physical AI interact directly with their physical environment, react to changes, and act independently. Sensors, data fusion, and learning algorithms form the basis for precise interactions, real-time planning, and the reliable execution of complex tasks.
In practice, this means that robots adapt flexibly to changing processes, driverless transport systems navigate safely even in unstructured warehouse environments, and assistance systems tailor their support to people depending on the situation. This results in self-optimizing systems that not only work faster and more precisely, but also increase the resilience of entire logistics networks.
Their potential goes far beyond efficiency gains: AI robotics can open up new fields of application, enable data-driven business models, and contribute to sustainability, for example through zero-defect production, optimized resource utilization, or the reusability of components. But getting there requires more than just technological investments. Physical AI also raises new questions: How can the complexity of flexible automation be mastered? What regulatory guidelines are necessary? And how can we gain acceptance and trust among the people who will be working with such systems in the future?
How AI robotics is already creating added value today
At the same time, practical projects show that AI robotics is a real value-added factor that measurably increases efficiency, flexibility, and quality. In an experimental setup at a southern German car manufacturer, for example, employees are testing new AI-supported assistance systems for assembly and logistics. During order picking, their eye movements are recorded and analyzed using eye tracking. This enables the system to detect when a part is missing or a work step is not proceeding as planned and to emit visual or acoustic signals in real time. The result is fewer errors, a more reliable supply to production, and reduced physical and mental strain.
As part of the Fraunhofer flagship project “Empathic Robotics,” researchers are developing systems that recognize and respond to the physical and emotional states of employees. For example, during assembly work, robots register when a worker is in an ergonomically unfavorable position. The robot then adjusts its support by changing its movements or handing over tools. This results in safer and more productive collaboration between humans and machines.
There are also examples of a printing press manufacturer who, together with a provider of implementation services in data science, machine learning, and AI, has rethought inventory planning for consumables in printing companies. Instead of fixed order cycles, machine learning algorithms determine actual demand in real time. Delivery quantities and times are optimized in such a way that inventories are reduced, scheduling is relieved, and materials are always in the right place at the right time. The vendor-managed inventory model can thus be scaled to significantly more customers without the need for additional personnel.
Act now, shape the future
Because the advantages of AI robotics are so obvious, Prof. Dr. Katharina Hölzle is convinced: “The introduction of AI robotics must not be put on the back burner. We have to move away from being observers and start taking action. Because only those who actively test technologies will gain the experience that will make a difference later on.”
The first step must therefore be to Doing. Specifically, this means launching pilot projects, gaining insights, and building on successes. Secondly, the human factor must always be taken into account. Employees must be involved from the outset in order to create acceptance and build skills. Thirdly, cooperation is needed: according to the “system of systems” approach, data is shared, interfaces are created, and synergies between partners are exploited.
However, Hölzle does not see the responsibility lying solely with companies: “Politics, business, and science must work together to create the framework conditions that will enable Germany to remain at the forefront of international competition.” Baden-Württemberg could lead the way as a model region, as it offers ideal conditions for this: a dense research landscape, strong relevant technology companies such as LAPP, many robot manufacturers, and an innovation-friendly ecosystem. Hölzle is certain that the path from individual pilot projects to widespread implementation will be worthwhile: “We are only at the beginning of a development that will fundamentally change production and logistics. Those who set the right course now will benefit in the long term.”