What is the difference between an AI agent and a workflow?

An AI workflow follows a defined sequence of steps, while an AI agent can decide dynamically what to do next based on the goal, current state, and results of previous actions.

Both can automate multi-step tasks, but they differ mainly in how much of the execution path is predetermined.

AI workflow

A workflow is usually designed in advance.

It may look like:

Step 1 → Step 2 → Step 3 → Step 4

For example:

1. Receive a support ticket.
2. Classify the ticket.
3. Retrieve the customer record.
4. Generate a draft response.
5. Send the draft for human review.

The system follows the defined path or a set of predefined branches.

Workflows are useful when the process is predictable and the required steps are already known.

AI agent

An AI agent is usually given a goal and allowed to determine some of the steps needed to reach it.

A simplified pattern is:

Goal → Observe → Decide → Act → Observe result → Decide again

For example, an agent asked to investigate a customer issue might decide to:

1. Read the ticket.
2. Search the knowledge base.
3. Check the customer's account.
4. Notice that information is missing.
5. Query another system.
6. Re-evaluate the issue.
7. Choose the appropriate next action.

The exact sequence may not be known before execution starts.

The key difference

The main distinction is where the decision-making happens.

In a workflow, the developer usually defines the execution path:

> If A happens, run B. If C happens, run D.

In an agent, the system can choose among available actions at runtime:

> Given the goal and current information, what should I do next?

This makes agents more flexible, but also less predictable.

Quick comparison

| Workflow | AI agent | | --- | --- | | Execution path is mostly predefined | Execution path can be determined at runtime | | Good for predictable processes | Useful for tasks requiring adaptation | | Decisions are largely encoded in rules or branches | Decisions can be made dynamically | | Usually easier to test and control | Usually requires stronger safeguards and monitoring | | Often executes a known sequence | May choose different sequences for similar tasks |

Workflows can contain agents

A workflow and an agent are not mutually exclusive.

For example, a larger workflow might contain an agent as one step:

Receive request → Validate input → Agent investigates → Human approval → Send result

Similarly, an agent may call predefined workflows as tools when it needs to perform a reliable business process.

This combination is common because workflows provide control while agents provide flexibility where fixed logic is difficult to define.

When is a workflow enough?

A workflow is often sufficient when:

• the process is well understood
• the same steps are repeated frequently
• branching rules can be defined clearly
• predictability is more important than flexibility

An agent becomes more useful when the next step depends heavily on changing context and cannot be fully specified in advance.

In short

A workflow executes a predefined process, while an AI agent can dynamically choose actions while working toward a goal.

Workflows emphasize control and predictability. Agents emphasize adaptation and runtime decision-making. Many practical systems combine both.