Good AI automation candidates are repetitive workflows with clear inputs, approved data, measurable outcomes, defined exceptions, and human review where mistakes matter.
Good AI automation candidates are repetitive workflows with clear inputs, approved data, measurable outcomes, defined exceptions, and human review where mistakes matter. The examples below are illustrative. Complexity and security depend on the actual systems, data, volume, and requirements.
Sales examples
1. Lead categorization — Medium
Problem: inquiries arrive as inconsistent free text. AI role: classify intent and urgency. Human role: define categories and review exceptions. Security: minimize customer data and prevent broad CRM access.
2. Follow-up drafts — Low
Problem: timely replies are difficult. AI role: draft from approved notes. Human role: verify accuracy and send. Security: keep confidential details out unless approved.
3. CRM routing — Medium
Problem: leads reach the wrong owner. AI role: interpret the request. Human role: set territory and exception rules. Security: restrict writable fields and validate record IDs.
4. Appointment intake — Medium
Problem: scheduling requires repeated questions. AI role: collect required context and propose slots. Human role: handle exceptions. Security: limit calendar visibility.
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Customer-service examples
5. Request classification — Low
AI labels an incoming request; people define labels and correct ambiguity. Avoid exposing unrelated tickets.
6. FAQ assistance — Low
AI retrieves answers from approved content; people maintain sources and receive escalations. Require source links and uncertainty handling.
7. Escalation detection — Medium
AI flags potential urgency or dissatisfaction; people make the final priority decision. Do not treat sentiment as an infallible judgment.
8. Ticket summaries — Low
AI summarizes long histories; technicians verify details. Restrict access to the assigned customer or queue.
Operations examples
9. Document routing — Medium
AI classifies documents; a fixed workflow routes approved types. People handle uncertain or sensitive documents. Validate destinations.
10. Recurring reports — Medium
AI summarizes approved source data; owners check completeness and context. Use read-only sources where possible.
11. Approval preparation — Medium
AI assembles the request and missing information; authorized people approve. The AI should not grant its own approval.
12. Task creation — Medium
AI extracts action items; a workflow creates tasks after validation. People confirm owners and due dates.
Administrative examples
13. Meeting summaries — Low
AI drafts decisions and action items; attendees correct the record. Control transcript access and retention.
14. Data-entry assistance — Medium
AI extracts fields; validation checks format and people review exceptions. Prevent writes to unrelated records.
15. Email triage — Medium
AI proposes category and priority; users retain control over deletion and sensitive replies. Mailbox access should be narrowly scoped.
Marketing examples
16. Content drafts — Low
AI creates a first draft from an approved brief; a person verifies claims, tone, rights, and accuracy.
17. Content repurposing — Low
AI adapts an approved source into channel-specific drafts; a person reviews each audience and platform.
18. Review-response assistance — Low
AI drafts a courteous response; a person checks privacy and sends. Never disclose customer details publicly.
Knowledge and phone examples
19. SOP and policy retrieval — Medium
AI searches approved internal sources and cites them; owners keep documents current. Use least-privilege folder access.
20. Call intake and missed-call follow-up — High
A voice workflow collects context, routes the caller, or prepares follow-up; people handle sensitive and unusual calls. Review disclosure, recordings, consent requirements, identity, and escalation for the actual use case.
How to prioritize these examples
Rank potential impact, implementation complexity, security risk, human oversight, estimated time savings from actual process data, dependencies, and readiness. Use Business AI Automation for technology-neutral workflows, Microsoft 365 AI Workflow Automation for Copilot and Power Automate intent, and AI Integrations when system connectivity drives the design.
A structured AI Opportunity Assessment helps identify the first workflow worth improving rather than selecting a tool first.
Recommended resources
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FAQ
Quick answers to common questions.
Start with a frequent, low-ambiguity process that has a clear owner and measurable baseline, such as intake classification, routing, recurring summaries, or draft assistance.
No. Fixed rules are often more reliable. Use AI when interpretation, classification, summarization, or drafting adds value.
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