How can AI security go from cost center to value driver in retail? In this episode, we use the blog “Best 10 AI-Powered Security Solutions Recognized for Boosting Retail ROI” (https://alphavision.ai/blogs/axis-integration/best-10-ai-powered-security-solutions-boosting-retail-roi) as our playbook. We unpack the top platforms, dig into real use cases, and offer guidance for retail teams looking to modernize security and operations.
Context: rising theft, fraud, and operational inefficiency make AI security a must, not a luxury
Deep dive on how AI transforms surveillance from passive recording into proactive alerting and deterrence
Differentiating factors among the 10 platforms: hardware vs software-led, cloud-native vs hybrid, plug & play vs custom integration
Use-case examples:
• Using POS correlation to flag suspicious refund/voids and trigger video lookup (Genetec, Verkada)
• Instant search across multiple stores (“Appearance Search”) to trace an individual’s path (Avigilon)
• Retro-fitting AI to existing installations via appliances (Spot AI)
• Offloading processing to edge cameras to reduce bandwidth (Hanwha)
Common pitfalls and risk mitigation:
• Network constraints undermining cloud systems
• Over-alerting fatigue need for smart filtering
• Cost creep in subscriptions or per-camera fees
• Ensuring data privacy, especially with analytics (face, LPR)
Steps to adopt:
• Benchmark current shrink & incident metrics
• Run side-by-side pilots for 2–3 competing systems
• Define KPI targets (loss reduction, labor savings, alert response)
• Scale phased by region, store type, or loss risk
Loss prevention and retail security executives
IT and digital transformation leads in retail
Integrators and vendors serving retail chains
Retail operations managers seeking efficiency gains
Analysts watching AI / retail technology trends
