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Retail Reinvented: 10 AI Security Systems Driving Higher ROI

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Manage episode 511272557 series 3684503
Content provided by UniviewNVR.com Podcast. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by UniviewNVR.com Podcast or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

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.

Key Takeaways
  • 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

Who Should Listen
  • 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

  continue reading

60 episodes

Artwork
iconShare
 
Manage episode 511272557 series 3684503
Content provided by UniviewNVR.com Podcast. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by UniviewNVR.com Podcast or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

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.

Key Takeaways
  • 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

Who Should Listen
  • 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

  continue reading

60 episodes

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