Retailers are turning to generative AI in many ways, such as creating web copy and conversational customer service chatbots, but little has been discussed about the tool’s potential to support loss prevention teams.
A study from Salesforce and the Retail AI Council found that 20% of retailers actively use generative AI, which is deemed a “realization” phase in the study, while 30% are in an “execution” phase. The report stated that leading uses support customer service (34%), such as chatbots, as well as marketing (30%) and store operations (30%).
As retailers grow more comfortable with generative AI, there are uses to explore that can specifically address shrink and the rise of organized retail crime (ORC). Some potential uses include providing loss prevention specialists with faster analysis of retail crime cases and helping to create stronger case files. The more retailers invest in the technology, the more they will be able to innovate within their loss prevention strategies and protect their overall profits.
Two Trends Collide: ORC Meets GenAI
Without a doubt, generative AI and ORC have been two topics driving headlines over the last year, as the retail industry grappled with understanding both.
For generative AI, the technology is expected to bring in more than $400 billion annually to the retail sector, according to McKinsey & Co. Of course, much of this money is tied to powering new automated workflows within marketing (personalizing content at scale), R&D (producing product concepts), software engineering (faster coding), and customer service (natural language chatbots), according to McKinsey & Co. Furthermore, loss prevention innovation will add to the growth of the technology.
Meanwhile, ORC is expected to continue hampering total retail losses. Capital One Shopping reports that shoplifting alone could cost retailers more than $150 billion by 2026, as ORC syndicates become savvier. Additionally, the Department of Homeland Security estimates that ORC costs federal and state governments roughly $15 billion in lost tax revenue, which is recouped by passing high prices onto consumers, hitting them in their wallets with more than $500 annually in additional costs.
Now, at the intersection of rising ORC and increasing interest in generative AI, retailers have an opportunity to improve how loss prevention teams innovate and fight back against retail crime.
GenAI Tactics to Boost Loss Prevention
Loss prevention specialists already depend heavily on technology to help find ORC groups and support investigations, but generative AI can be a functional co-pilot to work with other solutions.
Together with traditional AI models, data from RFID tags, computer vision cameras, and more, generative AI can give retailers an additional boost that accelerates the process. Some immediate benefits that generative AI provides include:
- Linking Cases: Generative AI can sift through mountains of retail data and incident reports to identify and link cases of ORC. Retailers can potentially link enough cases to a single ORC group to meet the felony theft threshold limit and charge them for more serious crimes. The minimum threshold depends on the state. For example, in Illinois, any theft exceeding $300 is subject to a felony charge, while in Washington, theft must exceed $750 to be considered a felony.
- Analyzing Reports: Generative AI has the ability to read through complex transaction data, summarize findings, and deliver recommended, actionable results. It does this for any user, democratizing the data and investigation process. Using a retail-focused, natural language model, generative AI prompts conversational queries that walk loss prevention specialists through an investigation.
- Supporting Law Enforcement: Just as generative AI can analyze and recommend insights, the technology can summarize specific elements inside an investigation to better support law enforcement. For example, the technology can generate detailed summaries of evidence inside a report for law enforcement, including video summaries. Law enforcement can also collaborate and rely on generative AI capabilities within reports. By giving them AI-powered optimized search, loss prevention investigators and law enforcement can collaborate to find ORC syndicates linked by specific details, such as the weapons used or items stolen.
At its core, generative AI accelerates the investigation process for loss prevention specialists and the law enforcement teams they work with. Linking cases and evidence, and building a bigger fight against ORC rings, can ultimately reduce retail loss.
What’s Next: Expanding Use Cases
As a new year dawns, retailers will prepare to increase adoption of generative AI tools in all facets of the organization. Certain job functions, like developing copy for marketing and analyzing data for the supply chain, might be farther along, but leveraging generative AI to support loss prevention departments and protect profits should have staying power. Companies will build case studies and slowly adopt generative AI into their loss prevention strategies.
Innovation powers loss prevention, addressing shrink and retail crime. Generative AI is a natural fit that can help companies identify ORC habits, build cases against them, and support law enforcement faster.
A product manager and AI expert with Appriss Retail, Sholan Narine has experience in building retail analytics and loss prevention solutions. Narine brings a deep understanding of how AI can transform incident management and fraud detection. At Appriss, he is driving innovation with products that empower retailers to manage investigations more effectively, leverage AI-powered insights, and take decisive action against ORC groups. His work aims to make complex data actionable and help retailers protect their profits.