AI agents follow a structured workflow, starting with goal setting and task planning. They then collect relevant data from multiple sources and use machine learning models to make decisions. After executing tasks, AI agents monitor outcomes, incorporate feedback, and adjust their strategies. This ongoing learning process enables AI agents to enhance their performance and tackle increasingly complex tasks more efficiently over time.