Read any textbook on the difference between generative and discriminative models and you'll usually find the explanation is usually less than intuitive. One of the better explanations I've read  is the following analogy: you are talking to someone who is speaking a language you don't understand. Your task is to figure out what language they are speaking (without the use of Google Translate!). You have two options:
As you may be able to tell from this simple analogy. discriminative methods are much simpler. But there are situations when you might want to use generative methods instead. For example, generative models are much better for finding missing values (i.e. they can generate data). However, if classification accuracy is your goal, a discriminative method, which "discriminates" (classifies) is likely the better choice. In sum:
 Jebara, T. (2019). Machine Learning Discriminative and Generative. Springer.