Retailers see real ROI from AI when insights translate directly into loss prevention actions.

At Gatekeeper Systems, we know the term “AI” gets added to nearly everything these days, from ChatGPT to $3,500 toasters (really) to many, many loss prevention solutions. We also know retailers must be able to answer fundamental questions about artificial intelligence LP solutions, including: “How did AI actually move our P&L needle in 2025, and what did those high-ROI use cases have in common?”

Retail clients who use our AI-driven FaceFirst software have detailed ROI metrics instantly available to answer those questions precisely. FaceFirst is the industry-leading facial recognition solution that helps retailers prevent loss and enhance store safety and security.

FaceFirst delivers proven results. Specifics may vary, but our clients report that the ROI is clear, sustained, and frequently outperforms their forecasted expectations. For instance, a grocery client realized an average loss reduction of $80K per store after deploying FaceFirst.

Clients can track multiple metrics in the FaceFirst dashboard, so common elements come into clear focus enterprise-wide. Here are a few other ROI-related stats reported by our retail clients and the Loss Prevention Research Council:

$225,000 fraudulent slip and fall claim disproved in hours, which also saved associated legal fees
76% reduction in theft events upon deployment, with most offenders deterred without incident
26% of known offenders targeted six or more client stores, with other criminal behavior patterns (thefts or incidents by day of the week, time of day, stores, cities, and states) identified for human analysis and response
8 times investigative efficiency for FaceFirst-assisted investigator with 4 times the case value and 2 times the number of incident locations identified

It’s clear that combining AI, computer vision, and human intelligence elevates security operations, reduces the investigative hours required to build criminal cases, and helps protect retailers’ bottom lines. For details, click here.