Use escalate to human for the user-facing route from AI, automation, chatbot, or self-service into a human channel; handoff summary for the context packet received after transfer; chat interface for the whole conversation surface; review queue for staff triage of many escalated items; human approval gate for authorizing a specific paused automation step; and recommended next action for optional guidance that may include escalation.
Use escalate to human for the user-facing route from AI, automation, chatbot, or self-service into a human channel; handoff summary for the context packet received after transfer; chat interface for the whole conversation surface; review queue for staff triage of many escalated items; human approval gate for authorizing a specific paused automation step; and recommended next action for optional guidance that may include escalation.
Practice the judgment: Imagine this situation: Talk to human restarts the bot, hides unavailable routes, or deflects to irrelevant suggestions after repeated AI failure. Write the person's goal, choose one of these patterns, and show the state that helps the person continue. Use the decision rules and source trail below to explain your choice.
Review the underlying principle →| Dimension | Escalate to human | Handoff summary | Chat interface | Review queue | Human approval gate | Recommended next action |
|---|---|---|---|---|---|---|
| UI or UX | UI + UX - Control and recovery path that transfers an AI, automation, or self-service case to a human channel or queue | UI + UX - Concise transfer packet for responsibility, conversation, case, or task context | UI + UX - Multi-turn conversation surface with transcript, composer, assistant responses, and conversation history | UI + UX - Actionable queue for triaging many items that need human review | UI + UX - Runtime checkpoint that pauses AI or automation until an eligible human authorizes the next step | UI + UX - Context-sensitive workflow action suggested for the user's current record, case, conversation, or task |
| UI guidance | Render escalate to human as an explicit route out of AI or automation, with trigger reason, eligibility, destination, expected wait, context shared, privacy boundary, and what happens to the current conversation, task, or run. | Render handoff summary as a transfer packet that names sender, receiver, transfer reason, current status, source object, generated or updated time, summary structure, next action owner, urgency, risks, and links back to transcript, ticket, log, case, or source records. | Render chat as an ordered transcript with visible user and assistant roles, turn boundaries, timestamps or relative position, current draft composer, submitted prompt, response status, source or tool indicators, and conversation-level controls. | Render review queue as an actionable worklist with queue scope, counts, filters, sort order, row reason, owner, priority, age or SLA, status, preview context, selection, and row actions. | Render a human approval gate as a paused automation checkpoint with the proposed action, tool or workflow step, triggering rule, risk level, payload snapshot, requester or agent, approver eligibility, timeout, and explicit approve, reject, edit, cancel, or bypass controls. | Render the recommended next action as a bounded suggestion card or action slot that names the action, trigger context, expected outcome, owner, due time or urgency, eligibility status, and why the system is suggesting it now. |
| UX guidance | Use escalate to human when the user needs human judgment, empathy, authority, accountability, exception handling, or support beyond what the AI or automation can safely complete. | Make the transfer trustworthy by exposing what is known, what is unresolved, what was attempted, what the receiver must do next, which facts came from source records, what is stale or generated, and which details are hidden by permission or policy. | Use a chat interface when users need a multi-turn assistant conversation where later prompts can depend on earlier turns, responses can be inspected or continued, and conversation history can be saved, resumed, deleted, or limited by policy. | Use review queue when a team repeatedly processes a changing set of tickets, comments, pull requests, content items, cases, requests, or records that require human inspection and action. | Use human approval gate when automation is ready to act but policy, risk, confidence, cost, access, publication, deployment, customer impact, or legal consequence requires a human decision before execution continues. | Keep recommended next action separate from broad recommendations, task lists, primary buttons, assignments, approvals, and review queues because it is optional, contextual, explainable, and directly tied to the current work state. |
| Good UI | An AI support chat shows Talk to a human after failed self-service, explains that transcript and account context will be shared, offers Live agent or Create ticket, and shows estimated wait. | A support conversation handoff shows customer, issue, AI steps already attempted, account status, reason for escalation, current sentiment, open question, next action, queue, owner, and source transcript link. | A research assistant chat shows user and assistant bubbles, turn numbers, source chips, streaming status, Stop, Copy answer, Regenerate, New chat, and a conversations list with the active chat title. | A moderation queue has Held, Likely spam, Reported, and Escalated tabs, row evidence, policy reason, reviewer claim state, approve/remove/escalate actions, and bulk-action preview. | An AI support agent pauses before issuing a refund, shows the proposed amount, customer, policy match, confidence, source grounding, approver role, timeout, Approve refund, Edit amount, Reject, and Stop run controls. | A support case sidebar recommends Send refund-policy article because the customer asked about a refund twice, shows confidence, source snippets, and opens a draft for review. |
| Bad UI | The UI says Transfer started but hides destination, queue status, wait time, shared context, and whether a human has actually accepted. | A generated summary omits a blocker or invents a resolution. | A conversation auto-scrolls to a new answer while the user is reading an older cited turn, then hides the old prompt after regenerate. | The most urgent or oldest item is buried by default sort. | A reviewer can approve an automation run after the action already executed, making the gate only decorative audit text. | Required onboarding tasks and optional suggestions are mixed in one list labelled Next best actions. |
| Good UX | A user requests human review outside business hours; the product creates a ticket, confirms SLA, preserves attachments, and explains how to return to the conversation. | A night-shift operator accepts a case handoff, checks open tasks and contingency notes, asks one clarification question, and confirms responsibility. | A user asks for a policy summary, follows up with Compare that to the renewal clause, sees that the second answer used the first answer and selected file, then exports the two-turn transcript. | A reviewer claims the oldest SLA-at-risk ticket, opens a preview, assigns it to Billing, returns to the queue with the row removed, and lands on the next oldest item. | A billing lead opens the paused refund gate, sees that the amount is under policy but source grounding is partial, edits the refund to the verified amount, approves, and the agent resumes only that step. | A representative reviews the suggested reply, sees that it was triggered by customer intent and a matching knowledge article, edits the draft, and sends it. |
| Bad UX | The product hides live-agent unavailability until after the user waits. | A receiver gets an assignment notification and must read 80 chat messages to learn why the customer is blocked. | Latest answer is disconnected from the prompt and context that produced it. | A reviewer marks a pull request reviewed from an old queue row after the author pushed new commits and re-requested review. | A human approves a stale agent action from email and the agent applies it to a different customer state. | A user accepts a suggested discount and only afterward learns it changed contract terms. |
| Best fit | The product can route to a staffed or asynchronous human channel and honestly show availability, wait, and fallback. | Responsibility, context, or conversation control transfers to another person, team, queue, shift, AI agent, live agent, or system. | The user needs a back-and-forth assistant conversation with follow-up questions and answer refinement. | A team or individual repeatedly reviews many independently queued items. | An AI agent, workflow, deployment, or automation is ready to perform a high-impact step and must pause for human authorization. | Users are working in a record, case, conversation, or workflow where choosing the next action is costly or error-prone. |
| Avoid when | The task is fully resolved by self-service and a human route would be decorative or misleading. | The page only needs key facts for the same reader. | The task can be completed with a single structured prompt box, form, or command. | The task is a single request moving through a governed approval route. | The action has already happened and users only need an audit log. | The action is always required and should be a task, validation, or workflow gate. |
| Required state | Available human route state with reason, destination, estimated wait, and shared context summary. | Default handoff summary with sender, receiver, reason, status, and source object. | Empty new chat with conversation title, mode, history or retention status, and a labelled composer. | Queue loading and count state | Paused gate state with proposed action, payload snapshot, reason for gate, and run context. | Recommended action state with action title, reason, evidence, trigger, consequence, and accept or review path. |
| Accessibility burden | Expose route type, destination, wait, queue state, context sharing, consent, cancellation, fallback, and human joined status as text. | Use clear headings for situation, background, assessment, recommendation, actions, risks, source links, and receiver status. | Expose the transcript as an ordered region and use a sequential update strategy such as role=log for appended messages where appropriate. | Use labelled queue name, count, filters, sort, group, row status, selection, preview, and action controls. | Expose gate status, proposed action, target, payload summary, risk, approver rule, timeout, and current run state as text. | Use a labelled region or card heading that identifies the suggestion as recommended, optional, and scoped to the current work object. |
| Common misuse | Hiding the human route after the AI fails repeatedly. | Sending only an assignment notification and calling it a handoff. | Auto-scrolling during streaming while the user is reading an older message. | Treating review queue as approval workflow and hiding many-item workload controls. | Using a post-action audit record as if it were a pre-action human gate. | Hiding why the action was suggested, what evidence was used, or what will change. |