To generate automated summaries of news articles using an Azure OpenAI model, fine-tuning the model on a dataset of news articles and their summaries (C) is the most effective approach. This allows the model to learn the patterns and techniques required for summarization. Using a single, broad prompt (A) may not provide enough guidance for the model to generate focused summaries. Implementing a text preprocessing system (B) can be helpful but does not directly address the need for training the model on the summarization task. Limiting the model's summaries to a predefined set of topics or keywords (D) may restrict its ability to handle a wide range of articles.