AI agents are intelligent systems that can operate on their own by understanding user inputs, analyzing data and performing actions that align with a defined goal. When we ask what are AI agents, they can be described as software entities that observe their environment, make decisions and complete tasks without constant supervision. This makes AI agents useful for automation, data analysis, customer support and product development across many industries. To understand how AI agents work, it helps to look at the steps they follow. First, an AI agent collects information from the user or from connected systems. It then processes that information using machine learning and language models to determine the right action. After deciding what needs to be done, the agent executes the task using the tools or applications linked to it. Advanced AI agents can break large tasks into smaller actions, evaluate the results and improve their performance over time. There are different types of AI agents, and each one is designed for a specific way of working. Reactive agents respond instantly to inputs without storing past data. Model based agents use stored knowledge to plan more accurately. Goal oriented agents focus on achieving a specific outcome through structured decision making. Learning agents study their past actions and adapt their approach to deliver better results. Overall, AI agents have become an important part of modern digital systems. They help organizations reduce manual work, improve accuracy and support faster and smarter decision making.