AI can reduce the time retail loss prevention teams spend finding footage and reviewing routine activity. That creates a management decision: what should the team do with the capacity it gains?
Retailers can use that capacity to cover more stores, investigate additional risks or reduce the resources required for existing work. Each choice changes how the team operates, which skills it needs and how its performance should be measured.
Less Time Finding Video and Screening Routine Events
Traditional POS investigations involve repeated steps: identify an event, locate the relevant video and watch enough footage to understand what happened. Much of that work ends with a legitimate explanation.
Connecting POS events directly to CCTV video reduces the effort needed to reach the right footage. In our work at iCape, we measured a reduction in retrieval time from ten minutes to five seconds. This measures access to the relevant video, rather than the time required to complete an investigation.
AI video analysis changes the next step as well. It can assess the physical activity around a POS event and help determine which events need human review.
For example, a cancelled transaction may be legitimate. A cancellation where video indicates that cash was received beforehand deserves closer examination. This allows teams to focus their attention on a more relevant set of events across the enabled store network.
The result is more capacity for work that requires human judgment.
What Should Loss Prevention Teams Do with the Time Saved?
Faster review creates several options. A retailer may maintain its current scope with fewer resources, extend regular checks to more stores, add theft scenarios or investigate other parts of the business.
At a fashion retailer we work with, the loss prevention team previously reviewed five anomalous stores each month through sampled checks. The same team now conducts regular, focused checks at 45 stores.
That changes the team’s reach. Stores can receive attention because of specific events, even when their overall transaction patterns appear unremarkable.
At a candy retail chain, time released from till-related work allowed the same people to examine warehouses as well.
These examples show why leaders should decide how to use the time saved. A shorter review process creates an opportunity; the team’s priorities determine the business value.
A practical starting point is to identify the work currently left undone. Which stores rarely receive attention? Which risks are known but seldom checked? Which investigations are delayed because routine screening consumes the team’s time?
Those gaps can become the team’s next priorities.
Who Can Review the Video?
AI and POS video integration also change the skills required for everyday review.
Previously, reviewing video required employees to calculate time differences and have considerable patience for repetitive work. When relevant footage is immediately available and routine events have already been filtered, employees with less analytical experience can take on video review.
They still need training, sound judgment and clear instructions on when to escalate an event. A flagged event is a reason to investigate; it is not proof of theft.
This creates scope to distribute review work more widely, while experienced investigators focus on ambiguous events, evidence development and follow-up.
Who Gets the Most Value from the AI?
Alongside people who review video, retailers need employees who understand how the AI works and can challenge its decisions.
These employees need to understand retail operations and theft methods, assess whether a scenario captures the intended risk and recognize when its results require further examination.
Their role becomes particularly valuable when the retailer can add scenarios independently.
In iCape, customers can add scenarios themselves without depending on the supplier. Existing scenarios can already deliver substantial gains. More sophisticated employees can build on that foundation by identifying additional risks, configuring scenarios, testing the results and refining their use.
For example, a retailer may identify a recurring pattern that its current checks do not address. Someone must translate that operational concern into a useful scenario and assess whether the resulting events deserve attention.
The team therefore needs a balance of skills: people who can review footage consistently, and people who can develop and assess the way the system directs that review. In a smaller team, one employee may perform both roles.
What Should Leaders Measure Beyond Catches?
Confirmed theft cases remain important. But counting catches alone gives leaders an incomplete view of the team’s contribution.
A team may now examine more stores, review events sooner or identify a recurring process weakness. Those improvements deserve measurement, even before they produce a confirmed case.
Useful measures include:
Leaders should also distinguish system activity from employee performance. The number of alerts generated is a system output. An employee’s contribution lies in the quality of the assessment, the evidence developed and the action that follows.
Measures should reflect each role. A video reviewer, an investigator and an employee developing scenarios have different responsibilities.
Building the Team Around Its New Capacity
AI changes the workload and the decisions facing loss prevention leaders.
Routine review becomes easier to assign. Experienced employees gain time for investigations and broader coverage. Employees who understand the technology can expand the scenarios the retailer examines.
Getting value from that change requires deliberate choices about priorities, roles and measurement.
At iCape, we help retailers connect POS activity with existing CCTV and use AI video analysis to focus human attention. For loss prevention leaders, the next question is what their team can achieve with the capacity that releases.