| 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. | Use handoff summary when work, responsibility, or conversation context moves between people, teams, shifts, AI agents, live agents, queues, or tools and the receiver should not need to reconstruct the situation from raw history. | 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. | Use recommended next action when the user is already working in a case, conversation, record, or workflow and the system can propose the next concrete step that reduces decision effort without removing user judgment. |
| 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 support queue shows New triage, SLA at risk, owner, customer, status, priority, age, preview text, assignment, and next actions without opening every ticket. | 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 | A Help button restarts the bot with no human route even after repeated failure. | A ticket says Transferred to Billing with no reason, customer need, previous attempts, blockers, or next action. | A chat panel shows one undifferentiated wall of text with no user or assistant roles, no submitted prompt, and no visible conversation identity. | A review queue shows a flat list of titles with no reason, age, owner, status, priority, or action controls. | A banner says Human approval needed but does not show the tool call, payload, approver, timeout, or resume consequence. | A large Continue button is labelled Recommended without any trigger, reason, consequence, or alternative. |
| Good UX | A user reports that the AI cannot resolve a locked billing account; the product offers a billing specialist queue, shows two-minute wait, shares the transcript with consent, and updates when a human joins. | A live agent accepts a bot escalation, reads the handoff summary, sees the customer already tried password reset twice, confirms the account lock risk, and continues without asking the customer to repeat themselves. | 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 | A user types human repeatedly, but the assistant keeps asking clarifying questions and never reveals that live support is closed. | A receiver gets an assignment notification and must read 80 chat messages to learn why the customer is blocked. | A follow-up uses prior conversation context after chat history has been switched off, without explaining that current-session context still exists. | Two reviewers open the same unclaimed item, both act, and the second decision overwrites the first with no stale-row warning. | 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 | Users need a person because AI, automation, self-service, or scripted support cannot resolve the situation safely or acceptably. | 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. | There is no receiver taking over context or responsibility. | 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. | No recommendation state with normal workflow controls still available. |
| 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. | Treating chat as a large textarea plus latest answer with no durable turn identity. | Using an ordinary table with no review reason, urgency, ownership, or decision actions. | Showing Approve without the exact action, payload, target, risk, or resume consequence. | Calling a static primary button a recommended next action without context-sensitive logic or reason. |