Technical details about AI agents: Industrial AI agents are specialized software modules based on the principles of machine learning and artificial intelligence. These agents are programmed to independently perform specific tasks such as monitoring production processes, optimizing workflows or managing resources. An essential aspect of their functionality is the ability to process large amounts of operational data in real time and to draw conclusions from it to increase efficiency and reduce errors.

Interfaces and integration: A key issue is the integration of AI agents into existing industrial systems. Interfaces play a crucial role in this. For the agents to work effectively, they must be able to communicate seamlessly with different data sources and control systems. This is often achieved via API (application programming interface) interfaces, which provide a standardized way for different software applications to communicate with each other.

API interfaces: APIs enable agents to access and control a wide range of system functions without the need for deep intervention in the software architecture. For example, an AI agent can access production data via an API, analyze it and, based on the analysis, suggest or directly initiate adjustments to the production parameters.

A specific example of the integration of AI agents is the TIA Portal from Siemens, an engineering platform for the automation of manufacturing processes. Hadzalic describes how AI agents have been integrated into the TIA Portal.

Hadzalic describes how AI agents are integrated into the TIA Portal to provide engineers with assisted functions. These agents can, for example, support the code generation process, perform error analysis, or provide optimization suggestions for machine operation.

Future development and interoperability: The Siemens developer sees the future of industrial AI agents in further refinement of interoperability and autonomy. He emphasizes the importance of open standards and the development of interfaces that enable even tighter integration of AI agents into industrial systems. This would allow agents to serve not only as supporting tools, but as integral parts of the system, able to respond proactively and in real time to challenges.

Finally, the two discuss the challenges of developing and implementing AI agents, particularly with regard to security and data protection. He emphasizes that security aspects must be given high priority when designing the interfaces to ensure that the systems are protected against unauthorized access while also being able to function efficiently and reliably. The development of these technologies, according to the Siemens man, is only just beginning, but the potential for transformative change in industry is enormous.