Retail shrinkage — from shoplifting, employee theft, vendor fraud, and administrative errors — costs retailers 1.5–2% of revenue on average. For a $1M store, that is $15,000–$20,000 per year. AI can meaningfully reduce this.
AI for theft prevention:
Video analytics: AI analyzes security camera footage in real time, flagging behaviors associated with shoplifting (loitering in high-value sections, unusual movements at checkout) without requiring constant human monitoring.
POS anomaly detection: AI monitors transaction data for patterns that suggest employee theft — excessive voids, refunds without returns, sweethearting, and under-ringing. These patterns are nearly invisible to human managers but clear to AI.
Inventory variance analysis: AI compares received inventory to sold inventory and highlights variances that suggest shrinkage, directing physical inventory checks to high-risk areas.
Vendor compliance: AI checks incoming deliveries against purchase orders, flagging short shipments and substitutions.
High-risk time identification: AI identifies the times of day, days of week, and staff configurations associated with higher shrinkage — allowing you to deploy more supervision strategically.
Tools: Verkada (AI video analytics), Sightline (retail AI), and most modern POS systems have anomaly detection features.
What percentage of your inventory loss do you attribute to shoplifting vs. internal theft vs. administrative errors?