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AI makes decisions based on the algorithms and models that are programmed into it. These algorithms and models use a combination of data, rules, and statistical analysis to make decisions. 

For example, in a machine learning model, the AI system is trained on a large dataset and learns from patterns and correlations within the data. It then uses this learning to make predictions or decisions about new data that it encounters. 

In rule-based systems, the AI system is programmed with a set of rules and logical conditions that it uses to make decisions. These rules are typically based on expert knowledge or domain-specific information.

In both cases, the AI system uses a combination of data and rules to make decisions. However, the specific approach used will depend on the type of AI system, the task at hand, and the available data and resources.