With autonomous AI agents, Siemens aims to redefine industrial automation — machines that can think, decide, and act independently. But behind this technological progress lie major challenges: How autonomous should production be? And what role will humans play in the factory of the future? A closer look beyond the buzzwords — and at what’s truly at stake.
With the introduction of autonomous AI agents, Siemens aims to elevate industrial automation to a new level. What at first glance seems like another step toward digitalization could turn out to be a profound shift in industrial practice — with far-reaching consequences for production, work organization, and strategic management in the manufacturing world.
The new software agents Siemens recently introduced as part of its industrial portfolio operate autonomously, make decisions based on real-time data analysis, and are intended to independently optimize entire production processes in the future. Their foundation lies in machine learning, digital twins, and continuous networking within the manufacturing process.
The concept is not new — the industry has been experimenting for years with adaptive systems and learning machines. However, Siemens is pursuing a more radical approach with these autonomous agents: the systems are designed not only to assist but to actively intervene, control, and prioritize — without constant human operator involvement.
Pragmatism Instead of Vision
Siemens is explicitly not focusing on futuristic scenarios but rather on solving concrete production problems: increasing complexity, rising energy costs, skilled labor shortages, and fragile supply chains. The agents are designed to tackle situations where traditional automation reaches its limits — such as unexpected deviations, rapidly changing requirements, or the dynamic control of multiple production lines in real time.
Here’s an example: In a flexible manufacturing system, the AI agent detects a sudden spike in the energy consumption of a production line. Instead of waiting for predefined thresholds to be reached, the agent analyzes the cause, suggests changes to the production schedule, or automatically initiates adjustments — faster than a human could, and based on all available data.
Between Ambition and Reality
The term “autonomous” should still be approached with caution. Siemens also emphasizes that the AI agents are initially intended for use in clearly defined, limited application scenarios. Fully autonomous systems that freely make decisions over production processes remain a thing of the future. The agents operate under supervision, their interventions are transparent, and they can be overridden by humans.
Additionally, technological progress alone is not enough. Implementing such systems requires high data quality, robust IT infrastructures, and the trust of the workforce. Skepticism is especially prevalent in traditional industrial companies toward systems whose decision-making logic is difficult to understand.
A multilingual professional experienced in Europe, Canada, and China, Herbert has developed invaluable networks in the automotive and energy industries. He has led high-profile projects involving ENBW, Mercedes-Benz Group, Siemens Group, and the Fraunhofer Institute.