AI Agents & AI Workflows: Probabilistic Tasks and Human Review
What this domain tests
AI agents and AI workflows test whether you can separate probabilistic AI tasks from deterministic automation, choose the right AI capability, and keep a human in the loop.
Core rules and concepts
- monday AI adds AI actions and assistants to Work Management: summarizing updates, drafting text, categorizing items, extracting fields, translating, and sentiment or intent analysis.
- An AI agent is configured with instructions, knowledge, and permitted tools; it can be triggered by an automation and act on an item. An AI workflow chains agent steps, automation steps, and approval gates.
- AI usage consumes AI credits; availability and credit volume depend on plan or add-on. Outputs are generated, not calculated, so they need review.
- Agents inherit access boundaries: they should only read boards and items the configuring user can access. Use a human approval step before external sends or status changes.
Worked example
Incoming support emails create items. An AI agent classifies sentiment and drafts a reply, then posts the draft as an update; a workflow waits for a human to approve before sending. Reasoning: the agent handles language interpretation, the automation handles the trigger and approval routing, and the approval prevents an unverified send.
Traps
Treating AI output as deterministic; using an agent for exact arithmetic that a formula column should handle; forgetting credit consumption; skipping approval on customer-facing actions; and assuming an agent can bypass board permissions.