Over the past six months, there's been notable growth in deploying AI agents across enterprises, highlighting varied complexities in use cases and the balance between purchasing specific agents and developing bespoke workflows. The article explores the current state of AI agents, defining them as systems that integrate core application functions and workflow automation using LLMs. It discusses building considerations for agents, emphasizing user collaboration and task planning. Various agent types, including vertical, horizontal, and multimodal, are emerging, demonstrating significant value in enterprise applications such as streamlining software development, enhancing customer experience, and optimizing back-office operations. The narrative also outlines challenges in compliance, data management, cultural resistance, and the economics of agents, including emerging pricing models aligned with measurable outcomes. Finally, it provides insights into decision criteria for whether enterprises should build or buy AI solutions, and highlights the importance of practical applications and cultural integration in achieving successful deployments.