Understanding the different types of AI agents and how they work

Generative Artificial Intelligence (AI) has evolved from static chatbots to systems capable of reasoning and autonomous actions, transforming digital workflows and enhancing user experiences. AI agents, unlike traditional AI systems, can adapt independently, using components like perception, reasoning, action, and learning to achieve specific goals within digital ecosystems. These agents vary from simple reflex agents to complex multi-agent systems, each offering unique functionalities such as personalized content delivery, predictive tasks, and complex goal management. AI agents are customizable and scalable, making them suitable for diverse applications, particularly in content workflows where they automate and enhance content creation and personalization. Best practices for managing AI agents include optimizing setups to match agent strengths, incorporating human oversight, and ensuring explainability to maintain brand safety and accountability. Contentful offers an AI-powered platform that integrates these agents to automate and streamline digital content management, providing tools for asset tagging, multilingual content handling, and compliance checks, thereby enhancing efficiency and consistency in content delivery.