AI POS Evaluation: Questions to Ask Before Approving a Feature
Use a practical review checklist for AI-assisted POS functions, covering data quality, human oversight, deployment and measurable error rates.
An AI POS proposal should describe a specific function, not a vague promise of smarter retail. Ask what decision is being assisted, what information is required and how a wrong result is corrected. Product suggestions, forecasting and image recognition need different evidence and should not be approved as one undifferentiated feature.
Request a clear model of the service
Identify whether processing happens on the terminal or a remote service. Confirm data retention, permissions and any use of customer or staff information. Ask how the supplier evaluates accuracy and whether its test conditions resemble your store. An average score is not sufficient if important products or users experience a much higher error rate.
Set acceptance criteria
- Compare with the existing non-AI process using representative data.
- Measure false positives, missed cases and staff correction effort.
- Provide human review for consequential decisions.
- Test lost connectivity, model updates and rollback.
- Verify supported computing resources and software versions on the actual terminal.
Review after deployment
Monitor whether results change with stock, lighting or customer behavior. Keep an ordinary fallback and a route for reporting mistakes. Include subscriptions and review work in the cost assessment. AI should be retained because it improves a defined task with acceptable risk, not because the terminal can be marketed with a fashionable label.