An AI agent is a single AI worker handling one task or one kind of request. An AI workflow is the structure that coordinates several AI agents toward a shared goal, in a defined order, with context handed off between steps. The two terms get used interchangeably in AI marketing, but they describe different layers of the same system — an agent is a worker, a workflow is the plan that puts workers to use.
Defining "AI agent"
An AI agent, in practical terms, is an AI system scoped to perform a specific kind of task: answering a customer's question, drafting an email, looking up information, or taking a defined action within set permissions. An agent can be quite capable on its own — but by itself, it typically handles one request at a time, in isolation from whatever came before or needs to happen next.
Defining "AI workflow"
An AI workflow is what connects multiple steps — and often multiple agents — around an outcome. Instead of "answer this one question," a workflow might be "research this topic, synthesize the findings, and prepare a report," where each stage depends on the one before it. The workflow is the sequencing and handoff logic; the agents are what actually execute each stage.
A concrete side-by-side example
A single AI agent
A customer asks, "What's the status of my order?" An AI agent looks up the order and answers. One request, one response, done. If the next question is unrelated — "Can you also update my shipping address?" — the agent handles that as a new, separate request.
An AI workflow
A business goal is "research 40 at-risk accounts, draft personalized outreach, and summarize the responses." A research worker gathers account activity, an outreach worker drafts emails from that research, a person reviews and approves the drafts, and a summary worker compiles the responses once they come in — each step feeding the next automatically.
Why the difference matters for planning AI work
If your business need is answering a repeated type of question, a single AI agent may be enough — that's closer to a traditional AI tool. If your business need spans multiple steps, multiple systems, or multiple kinds of work that build on each other, you need a workflow that coordinates agents, not just one agent working alone. Knowing which one you actually need changes how you scope the project: a single well-configured agent is a smaller undertaking than a multi-stage workflow with handoffs and review points.
In practice, most useful AI workforce setups use both: individual agents configured for specific tasks, connected by a workflow that defines how those tasks relate to a larger goal.