AI agents are autonomous systems designed to perform specific tasks by perceiving their environment, processing data, and making independent decisions, thereby distinguishing them from traditional software. These agents are composed of various modules, including perception, reasoning, action, learning, and communication, and come in different types such as simple reflex, model-based reflex, goal-based, utility-based, and learning agents. Their real-world applications span numerous industries, from customer service and autonomous vehicles to virtual assistants and gaming, offering benefits like task automation, increased efficiency, improved decision-making, reduced costs, and competitive advantage. However, AI agents also present challenges, including multiagent dependencies that may cause widespread failures, infinite feedback loops requiring human oversight, changing human-AI interactions, and evolving cybersecurity risks that necessitate updated protection strategies. As AI agents continue to impact the way we work and interact with technology, balancing their benefits with security considerations remains critical.