A bot is an operating pattern
The term can describe a scheduled message, a rule triggered by an event, a suggested reply, an autonomous conversation or an analytic classification. These patterns differ in how much discretion the software has. Ask what event starts the work and who chooses the action.
A scheduler can send text that a person wrote earlier without generating a new response. A reply assistant can generate text while leaving the send decision to a person. An autonomous system may choose both the text and the moment to act. Product labels do not always make these distinctions clear.
Look for the decision boundary
Use the classifier to describe the workflow in ordinary terms. Whether content is generated and whether a person reviews it are useful distinctions. The result is a conceptual label, not a claim about a specific product’s implementation.
Check what happens when the inputs are incomplete or conflicting. A workflow may need to defer to a person rather than guess. Pay particular attention to requests to stop, disputes and actions outside the authorised scope. Record the cases where no automatic action should occur.
Verify the actual implementation
Ask the provider to demonstrate the trigger, decision, action and stopping behaviour. Check who can change the configuration and how changes are recorded. Distinguish the capabilities demonstrated today from features promised for later.
Classification does not establish permission to automate a platform. Review the relevant platform terms, access requirements and data handling. Avoid tools that require authority you do not have. If you adopt a workflow, begin with a limited scope and maintain a practical way to pause and inspect it.
Classify the action, not the marketing name
A single product can contain several automation patterns. A scheduled draft may be a human-approved workflow, while another feature in the same dashboard sends an event-triggered message without approval. Evaluate each proposed action separately. A claim that the overall product is “AI-powered” tells you little about the actual decision boundary.
Write the event-to-action chain in plain language: what happened, what information is read, what decision is made and what action follows. Then ask which step a person can inspect, amend or stop. This exposes hidden assumptions, such as a label automatically starting a sales sequence even though the user thought it was only a report.
Do not infer platform permission from the category. A workflow may be technically possible and still conflict with current platform rules or the account’s authority. Equally, the classifier cannot tell whether a specific subscriber is a bot or grant access to restricted content. Keep the taxonomy focused on systems you are authorised to evaluate.
| Pattern | What it does | Key control |
|---|---|---|
| Scheduled send | Executes approved content at a chosen time | Cancellation and current context |
| Event-triggered action | Acts when a defined event occurs | Eligibility and duplicate handling |
| Reply assistance | Proposes new text for a person to review | Visible context and send approval |
| Autonomous response | Generates and sends without per-message approval | Boundaries, pause and escalation |
| Analytic classification | Labels information for a report or queue | Data scope and correction of labels |
ILLUSTRATIVE WORKED EXAMPLE
A scheduled message is not necessarily an AI chatbot
Illustrative workflow: an operator writes a fixed introduction and schedules it for a later time. The system does not generate new text.
- Choose a schedule as the trigger and “No” for generated reply text.
- If the content and each action are approved by a person, the relevant workflow is human-approved. If the schedule executes without per-action review, it is a scheduled-send workflow.
- Now change the system to generate a response to an incoming conversation without approval. That is an autonomous response workflow with different control requirements.
The trigger and send decision define the operation more precisely than a product label.
Use the classifier to document the actual proposed action before comparing provider features.
Put it into practice.
Map a proposed workflow to an automation category. Classification is not permission to use it on a platform.
Classify a workflow ↗Bot workflow examples: triggers, decisions and actions →
Related questions
Are all bots generative AI?
No. A fixed schedule or a deterministic rule can automate an action without using a language model.
Does the classifier identify a real account’s bot?
No. It classifies the workflow you describe. It does not inspect accounts or determine who wrote a message.
Is automation always better than a person?
That depends on the task, context and observed outcomes. Automation changes where oversight is needed; it does not eliminate responsibility.
Original practical guidance prepared for Onlytool. Worked cases are illustrative, not measured customer results. This publication does not claim independent vendor testing. Methodology and disclosure.