Section 01
Repetitive work
- What tasks does your team repeat every day or week?
- Which emails, messages, or documents are written repeatedly?
- Which tasks require copying information from one system to another?
Checklist
The AI Automation Opportunity Checklist
A practical checklist for business owners who want to find high-value AI automation opportunities without exposing customer data or wasting money on hype.
- Find bottlenecks
- Rank opportunities
- Contain risk
- Select the first pilot
Self-assessment
Questions to help you find strong AI candidates.
The best workflows to automate are usually frequent, measurable, repetitive, and possible to pilot safely with approved data.
Section 02
Customer response delays
- Where do customers wait too long for answers?
- Which inquiries are common and predictable?
- Which requests require staff to search internal documents or systems?
Section 03
Sales follow-up problems
- Where do leads fall through the cracks?
- Are meeting notes consistently captured?
- Are follow-up emails and CRM updates completed reliably?
Section 04
Internal knowledge gaps
- What questions do employees ask repeatedly?
- Where are procedures, policies, and project history stored?
- Can new employees find answers without interrupting senior staff?
Section 05
Manual reporting
- Which reports are manually assembled?
- Which numbers come from multiple systems?
- What summaries do managers create repeatedly?
Section 06
Document-heavy workflows
- Which documents require repetitive review, summarization, or drafting?
- Where is important context trapped in proposals, contracts, forms, or notes?
- Which workflows slow down because teams cannot find or standardize information quickly?
Section 07
Admin and back-office drag
- Which workflows depend on spreadsheets, inbox triage, reminders, or manual status updates?
- Where do handoffs between teams create avoidable delays?
- What repetitive steps are consuming operating capacity without adding strategic value?
Section 08
Security and privacy risks
- What sensitive data would an AI system need to see?
- Who should be allowed to access AI-generated answers?
- Which actions require human approval?
- What needs to be logged?
Section 09
Data readiness
- Is the source data structured, approved, and accessible enough for a pilot?
- Do you know which systems or documents contain the information the workflow needs?
- Can the first version start read-only before writing back into core systems?
Section 10
First pilot selection
- Is the workflow frequent?
- Is the value clear?
- Is the data accessible and safe to use?
- Can the first version be limited in scope?
- Can a human review outputs before action is taken?
Interpret the list
What to do with the answers.
Once you identify likely workflows, rank them by business value, implementation complexity, data readiness, and security exposure.
Good pilot candidates
Look for workflows that happen often, consume real team time, use already-approved data, and can begin with review before automation acts on its own.
Poor pilot candidates
Avoid broad autonomous systems, unclear business value, messy data dependencies, and workflows where a first mistake would create high customer or compliance risk.
What to do next
Once you find two or three candidate workflows, rank them by value, security, integration complexity, and how quickly you can validate the result.
Book an AI Automation Audit
Found two or three likely workflows?
That is usually enough to make an audit worthwhile. The next step is to rank them, identify the risks, and define the narrowest useful pilot.