Скачать или смотреть What is an AI Workflow?

Two of the most common—and commonly confused—concepts are AI Agents and AI Workflows.

While both use artificial intelligence to get things done, they are fundamentally different tools designed for fundamentally different jobs.

The key insight is that their difference isn't about whether they use advanced AI like Large Language Models (LLMs). Many people believe that adding an LLM like ChatGPT to an automation automatically makes it an "agent," but this is a core misconception. As automation experts at Relevance AI note, "The presence of language models tells you nothing about which type of automation you're looking at." The real difference lies in how they make decisions.

Now, let's break down the single most important distinction between these two powerful approaches.

The Core Distinction: Predictions vs. Predefined Conditions

At their technical core, the difference between an AI agent and an AI workflow comes down to how each system decides what to do next.

• AI Workflows make decisions based on predefined conditions powered by code. They follow a fixed, predefined map of IF-THEN logic, perfect for tasks where the path is known and consistency is critical.

• AI Agents make decisions based on real-time predictions powered by a model. They are given a destination (a goal) but must figure out the best path to get there in real-time, adapting to new information as they go.

An AI workflow is a structured sequence of interconnected tasks where artificial intelligence powers one or more steps. Think of it as a sophisticated assembly line where AI components perform specialized jobs in a predefined order to achieve a business objective. While a workflow can be highly intelligent, its path is ultimately fixed.
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