Scenario modelling for AI is particularly at home in the fields of artificial intelligence, automation, big data and smart data. It describes a method for designing and testing different "what-if" situations for an AI. This allows you to test how well an AI reacts in different, even unexpected situations.
Scenario modelling trains an artificial intelligence to act flexibly. For example, an AI in a factory can be shown several scenarios: What happens if a machine suddenly breaks down? Or how does it react to a sudden change in the supply of materials? All of these situations can be simulated in the computer and the AI can learn from them without any disruptions occurring in reality.
The big advantage for companies: Risks can be recognised and processes made more secure. Scenario modelling for AI is therefore an important step in ensuring that intelligent systems become reliable and can also solve unusual problems independently.















