How to use this glossary
These definitions are written for practical workflow understanding. They are not legal, medical, safety, engineering, cybersecurity, compliance, financial, tax, child-care, veterinary, employment, or professional advice.
Core workflow terms
These terms describe how work moves through a process before, during, and after AI assistance.
| Term | Plain-language meaning | Why it matters |
|---|---|---|
| AI workflow | A work process that uses AI to support one or more steps, such as intake, classification, drafting, routing, review, escalation, or monitoring. | The workflow should show how work moves, not just which AI tool is used. |
| Workflow | A repeatable path that work follows from start to finish. | Clear workflows reduce confusion and make responsibility easier to trace. |
| Intake | The point where work enters a process, such as a form, email, ticket, message, alert, record, or document. | Poor intake creates poor downstream results, even if AI is added later. |
| Classification | Sorting work into categories, topics, types, risks, departments, or urgency levels. | Classification helps decide what happens next. |
| Triage | A first-pass sorting process that helps decide priority, urgency, route, or review level. | Triage helps overloaded teams focus attention where it is most needed. |
| Routing | Sending work to the right person, queue, team, system, or approval path. | Good routing prevents work from sitting in the wrong place. |
| Prioritization | Deciding what should be handled first, later, automatically, manually, or through escalation. | Prioritization helps teams manage limited time and attention. |
| Handoff | The transfer of work from one person, system, queue, or stage to another. | Weak handoffs are a common source of dropped tasks and unclear responsibility. |
| Workflow owner | The person or role responsible for how a workflow is designed, monitored, corrected, and improved. | AI should not make ownership disappear. |
| Input | The information, request, document, signal, alert, or record that enters a workflow step. | AI output depends heavily on the quality and limits of the input. |
| Output | The result produced by a workflow step, such as a summary, draft, classification, route, recommendation, alert, or decision record. | Outputs need review rules, quality expectations, and clear next steps. |
AI support terms
These terms describe common ways AI can assist work without becoming the only source of judgment.
| Term | Plain-language meaning | Workflow caution |
|---|---|---|
| AI-assisted workflow | A workflow where AI supports parts of the process while people or systems remain responsible for review, approval, and action. | Assistance should not be confused with full authority. |
| Automation | A system that performs a repeatable step according to rules or instructions. | Traditional automation is usually more fixed than AI-supported work. |
| Traditional automation | Automation based mainly on predefined rules, structured data, and predictable conditions. | It works best when the process is stable and the inputs are clear. |
| Agentic workflow | A workflow where an AI system may plan, call tools, take intermediate steps, or coordinate tasks within limits. | Agentic workflows need strict scope, permissions, logs, and human review rules. |
| Summarization | Using AI to condense emails, tickets, documents, transcripts, or records into shorter explanations. | Summaries can miss details and should be reviewed when the stakes are high. |
| Theme extraction | Using AI to identify repeated themes, complaints, issues, requests, or patterns across many records. | Theme extraction helps with signal, but humans should review important conclusions. |
| Signal vs. noise | The difference between information that matters and information that distracts or repeats. | AI can help filter noise, but filters can also hide important minority cases. |
| Drafting support | Using AI to prepare a draft response, note, summary, checklist, or document for human review. | A draft is not automatically approved or accurate. |
| Knowledge-base workflow | A process for creating, updating, reviewing, and using internal or public knowledge articles. | AI can help draft and organize knowledge, but stale information still needs review. |
| Multilingual triage | Using translation or language detection to help route, summarize, or review material in more than one language. | Translation errors can affect meaning, urgency, and fairness. |
Human review and control terms
These terms matter because AI workflows should preserve review, responsibility, evidence, and approval authority.
| Term | Plain-language meaning | Why it matters |
|---|---|---|
| Human-in-the-loop | A workflow design where a person reviews, approves, corrects, or supervises an AI-supported step. | Human review is essential for uncertain, sensitive, or high-impact work. |
| Review queue | A queue where items wait for human review before being approved, sent, escalated, or acted on. | Review queues make oversight visible and manageable. |
| Confidence threshold | A rule or score that helps decide whether AI output can move forward or needs human review. | Thresholds should be tested and monitored, not blindly trusted. |
| Overtrust | Relying too heavily on AI output because it sounds confident, polished, or fast. | Overtrust can let errors pass through the workflow unchecked. |
| Approval gate | A point where a person or authorized role must approve work before it moves forward. | Approval gates prevent AI from quietly authorizing everything. |
| Segregation of duties | Keeping important steps separated so one person or system does not control request, approval, action, and review. | AI should not collapse controls into one unchecked path. |
| Audit trail | A record of what happened, when it happened, who or what acted, and what evidence supported the action. | Audit trails help review mistakes, disputes, approvals, and changes. |
| Evidence preservation | Keeping the information used to support a workflow action, review, approval, or escalation. | Without evidence, it is harder to understand or challenge an outcome later. |
| Human override | A process that lets an authorized person stop, change, reject, or correct an AI-assisted step. | Overrides help keep people responsible when the workflow does not fit reality. |
| Approval routing | Sending work to the correct person or role for review and approval. | Routing should follow authority, risk, policy, and workflow design. |
Exception and escalation terms
Exceptions are not minor clutter. They are where workflow design proves whether it can handle real-world messiness.
| Term | Plain-language meaning | Workflow importance |
|---|---|---|
| Exception | A case that does not fit the normal workflow path. | Exceptions need clear handling instead of being ignored or forced through. |
| Exception handling | The process for identifying, routing, reviewing, and resolving unusual or non-standard cases. | Good exception handling prevents fragile automation. |
| Escalation | Moving work to a person, role, team, or authority with more responsibility or urgency. | Escalation keeps important issues from being trapped in a low-level queue. |
| Escalation path | The defined route an issue follows when it needs higher-level review or urgent attention. | Escalation paths should be known before something goes wrong. |
| Degraded mode | A restricted operating state used when normal systems, staffing, data, or controls are not fully available. | Degraded mode helps workflows keep operating more safely under pressure. |
| Emergency escalation workflow | A high-level process for alerting responsible humans or authorities when urgent risk is detected. | This site discusses emergency escalation only as workflow design, not emergency instructions. |
| Fallback path | A backup process used when the normal AI-assisted path fails, lacks confidence, or is unavailable. | Fallbacks stop the workflow from depending on one fragile path. |
| Return-to-normal workflow | The process for moving from emergency, degraded, or exception mode back to normal operation. | Returning to normal should include review, logs, correction, and approval where needed. |
| False positive | A case where the workflow flags something as a problem when it is not actually a problem. | Too many false positives can overload reviewers. |
| False negative | A case where the workflow misses something important. | False negatives can be more dangerous because the issue may never reach review. |
Monitoring and improvement terms
AI workflows should not be treated as “set and forget.” They need monitoring, correction, and version control.
| Term | Plain-language meaning | Why it matters |
|---|---|---|
| Workflow monitoring | Watching how a workflow performs over time, including volume, delays, errors, escalations, and outcomes. | Monitoring reveals whether the workflow is actually helping. |
| Workflow KPI | A measurable indicator used to evaluate workflow performance. | KPIs can track speed, quality, review burden, backlog, escalation rate, and correction rate. |
| Feedback loop | A process where outcomes, corrections, reviewer notes, or user feedback are used to improve the workflow. | Feedback loops turn mistakes and patterns into improvement. |
| Change control | A process for reviewing, approving, documenting, and testing workflow changes. | Changes to AI workflows can affect routing, review, risk, and responsibility. |
| Versioning | Keeping track of different versions of a workflow, rule set, prompt, template, model configuration, or process document. | Versioning helps explain what changed and when. |
| Spot audit | A sample review of workflow outputs or decisions to check whether the process is working properly. | Spot audits can catch hidden drift, overtrust, or quality problems. |
| Drift | A change in performance or fit over time as inputs, users, policies, or real-world conditions change. | A workflow that worked last month may not work the same way later. |
| Backlog | Work that has entered the workflow but has not yet been completed. | AI can help organize a backlog, but unresolved queues still need ownership. |
| Bottleneck | A step where work slows down, piles up, or waits too long. | Bottlenecks show where process redesign may matter more than adding another tool. |
| Continuous improvement | Regularly improving a workflow based on evidence, feedback, errors, and changing needs. | AI workflows should improve with use instead of quietly degrading. |
Care and safety workflow terms
These terms are included because AI workflows may appear in household, care, senior, child-facing, pet, facility, and safety-alert contexts. This site handles those topics carefully and at a high-level workflow-support level only.
| Term | Plain-language meaning | Important limit |
|---|---|---|
| Care-support workflow | A process that may help with reminders, alerts, check-ins, documentation, or escalation to responsible humans. | It does not replace qualified caregiving or adult responsibility. |
| Caregiver alert | A notification sent to a responsible person when a concern, reminder, or possible risk is detected. | An alert is not the same as professional assessment or emergency response. |
| Senior check-in workflow | A workflow that may support reminders, routine check-ins, unusual-activity alerts, or escalation to caregivers. | It should preserve dignity, privacy, human support, and appropriate review. |
| Child-facing AI workflow | A workflow where AI may interact with or support content around children, such as learning prompts or routine reminders. | It needs parent or guardian settings, privacy limits, safety review, and adult supervision. |
| Household safety alert workflow | A workflow that may detect or route alerts about household conditions such as alarms, environmental concerns, or unsafe situations. | It should not replace certified alarms, safe storage, adult supervision, or emergency services. |
| Pet monitoring workflow | A workflow that may support reminders, observations, alerts, or records related to pets. | It does not replace veterinary care or responsible pet ownership. |
| Privacy safeguard | A limit or control that reduces unnecessary collection, sharing, or retention of sensitive information. | Care and household workflows should not become unchecked surveillance systems. |
| Responsible human escalation | Sending a concern to a person who has responsibility to review or act. | AI should support escalation, not pretend to be the responsible adult or professional. |
Care and safety limit
This glossary does not provide medical, child-care, first-aid, veterinary, emergency-response, legal, security, or safety instructions. Care and safety terms are explained only as workflow-support concepts.