It all began in the 1950s with the Turing Test, when science first seriously engaged with the question “Can machines think?” Almost 70 years later, AI has arrived in companies.

 

The performance of AI models has multiplied exponentially compared to just five years ago.

 

Integrating AI into work or production processes can multiply value creation per dollar of input in many areas when comparing human vs. machine.

 

The automation of workflows in companies through agentic AI represents a milestone of our time. In contrast to conventional LLMs (Large Language Models) such as ChatGPT or Grok, agentic AI differs in essential ways from this generic AI.

 

Generic AI is reactive — it delivers output based on entered prompts and does not pursue goals on its own initiative. Agentic AI, on the other hand, has a significantly higher degree of autonomy: it pursues a goal, independently creates a plan to achieve that goal, executes these steps on its own, and has the ability to access systems outside its own program.

 

Compared to humans, AI agents — provided they are trained according to the process requirements and the data sources are of sufficiently high quality — can often solve tasks or subtasks faster, more consistently, in a standardized way, and at appropriate quality.

 

In practice, agentic AI is already being used in support, sales, finance, and marketing processes. The role of the human is clearly defined here: they make fundamental strategic decisions, set the goals and priorities for the AI agent, evaluate the execution, and grant approval or sign-off for certain actions. The human thus becomes more of a manager, while the AI agent autonomously takes over the execution role.

 

AI will transform the labor market in the near future. In areas with a high proportion of routine and standardized processes, the AI agent will take over these tasks. As the human role is limited to review and strategic direction, headcount requirements can decrease while productivity rises.

 

This shift is not limited to office environments — the manufacturing sector will also experience a paradigm change: especially for monotonous activities, shift work, or fluctuating capacity utilization, robots will take over tasks. This counters the skilled labor shortage and also delivers greater efficiency and productivity in suitable production lines. Robots do not get sick, deliver consistent quality, and can handle physically demanding and dangerous work.

 

In combination with artificial intelligence, robotics will take over entire production steps in the medium term, which also means greater planning reliability and availability for a company.

 

This does not mean humans will completely disappear from production lines — their role will shift toward supervision, maintenance, and process optimization.