What AI is / isn't
In plain words
Artificial intelligence is software that learns patterns from examples instead of following rules a programmer wrote out step by step. It is good at spotting patterns in large amounts of data and at producing fluent text, images or predictions. It does not understand a patient, carry responsibility, or know when it is wrong. It is a tool that makes guesses, sometimes very good ones.
Healthcare example (illustrative)
A drug-interaction checker that flags "warfarin + clarithromycin" because someone typed that rule into a table is not AI; it is ordinary software. A system that has seen many thousands of ECGs and estimates the chance that a new tracing shows atrial fibrillation is AI: nobody wrote the rule, it was learned from examples.
A little more technical
Most modern AI is machine learning: a model with many adjustable numbers is shown examples, compares its output with the right answer, and nudges those numbers to do better next time. After training, the model applies what it learned to new inputs. It can only be as good as the examples it learned from, and it has no built-in sense of when a new case is unlike anything it has seen.
Don't learn this yet
You don't need the mathematics of training to use or judge AI sensibly. Skip formal definitions, the history of AI, and debates about "general intelligence" for now.