AI workflows vs. agents: Similarities, differences, and when to use each

AI agents and AI workflows are both automation methods using generative AI, but they differ significantly in their structure and execution. AI workflows operate with a predefined set of steps that yield consistent and predictable results, ideal for tasks with well-defined inputs and outputs, such as support ticket routing or data processing. In contrast, AI agents function autonomously, deciding on actions and adapting to new information or conditions, making them suitable for open-ended or ambiguous tasks like research or customer support. While AI workflows are easier to implement and debug due to their deterministic nature, AI agents offer greater flexibility and can handle complex decision-making and dynamic scenarios. The choice between using AI agents or workflows depends on the specific needs of the task, with hybrid approaches often providing a balance of predictability and adaptability. As AI technology evolves, the trend is moving towards integrating both approaches to address diverse business challenges effectively.