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AI 101

AI in retail: How to improve security and operations

Smarter retail starts with better visibility. AI can help you catch issues faster, protect margin, and make day-to-day store operations easier to manage.

A man uses a tablet in a clothing store; text highlights an AI-driven retail loss prevention guide and $132 billion in annual retailer losses.

COO guide to AI-driven retail loss prevention and risk reduction

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Table of Contents

AI in retail is no longer just about chatbots and product recommendations. Retailers are using AI to tackle real challenges like theft, shrink, staffing shortages, compliance risks, and inconsistent store execution.

The need is growing. According to the National Retail Federation (NRF), retailers reported an 18% increase in shoplifting incidents in 2025, while McKinsey estimates AI could unlock $240 billion to $390 billion in value across the retail sector.

For many retailers, the biggest opportunity isn’t customer-facing AI – it’s AI that improves visibility into what’s happening in stores. By combining AI with video security and business data, retailers can identify risks faster, improve operations, and protect margin.

That’s where Solink comes in. Solink uses AI-powered video intelligence to help retailers reduce loss, improve operational consistency, resolve incidents faster, and make better business decisions. This guide explores how AI in retail works and where it delivers the greatest value.

First off, what is AI in retail?

AI in retail is the use of machine learning, computer vision, automation, and predictive models to help retailers detect patterns, understand behavior, and take action faster.

That can show up in many ways:

  • Predicting demand and improving inventory decisions.
  • Personalizing marketing and product recommendations.
  • Automating repetitive workflows.
  • Flagging unusual behavior that may indicate theft, fraud, or a process/compliance issue.
  • Turning video into searchable, actionable business data that increases profitability.

For operations and loss prevention teams, the most valuable part of AI is not the technology itself. It is the speed and clarity it brings to decisions that used to require hours of manual review.

Learn the top 6 AI solutions transforming retail in 2026

The main types of AI retail teams use

Artificial intelligence is evolving at an unprecedented pace, and it can certainly be difficult to keep up with what’s new. It’s important to understand the different types of AI and how they can benefit your retail business.

With that in mind, let’s take a look at some of the different types of AI and how they are applied to the retail industry. Some solutions you invest in may just use one of these types of artificial intelligence, while others may use multiple.

Queue detection and checkout optimization

Computer vision helps software interpret what is happening in images and video. In retail, that can support incident review, self-checkout oversight, queue monitoring, and store execution checks.

Machine learning

Machine learning helps systems identify patterns and improve predictions over time. In retail, it can help surface unusual transactions, detect repeat behavior, and highlight trends across locations.

Predictive analytics

Predictive analytics uses historical data to anticipate what may happen next. Retailers use it for demand forecasting, staffing, inventory planning, and risk detection.

Generative AI

Generative AI can help retailers summarize data, draft insights, and make information easier to access. In the back office and operations workflow, it can reduce manual effort and help teams move faster.

Retail AI agents

Retail AI agents go a step further by helping teams act on information, not just analyze it. Instead of simply surfacing a pattern or alert, an AI agent can help guide next steps, summarize what happened, and support faster decision-making across security, operations, and leadership teams.
In retail, that can mean:

  • Helping teams review incidents faster.
  • Summarizing key details from video, transaction, or event data.
  • Prioritizing the events that need attention first.
  • Supporting investigation workflows with less manual effort.
  • Turning raw data into clearer actions for store teams and leaders.

Retail AI agents are especially useful when retailers need to move quickly across many locations and cannot afford to spend hours sorting through noise. They are most valuable when they are connected to real retail workflows, business data, and video, so teams get context and direction, not just more information.

Discover the top use cases for your business for retail AI agents

Common retail challenges AI can help solve

It can be easy to get caught in the hype and adopt AI for the sake of adopting it. Don’t get caught into that trap. 

When looking for AI solutions, make sure you think about the most impactful, and highest priority, challenges that keep showing up in your stores. You want to invest money in solutions that deliver real impact and ROI for your business. 

Here are some of the most common pain points AI can help address for retailers:

Shrink and margin pressure

When losses are rising, the easiest response is often more manual review. But manual review does not scale well. AI helps teams focus on the highest-risk events first.

Inconsistent store execution

Even strong teams can struggle with consistency across locations. AI can help identify where standards are slipping so leaders can act sooner.

Slow investigations

When a team has to search through hours of footage, response times suffer. AI can shorten that process and help teams find the right moment faster.

Limited visibility across locations

Multi-location retailers often need a way to compare performance and spot issues quickly. AI helps turn location-level activity into actionable trend data.

Staff training gaps

Some incidents are caused by theft. Others are caused by inexperience or missed process steps. The combination of AI and video security helps distinguish between the two so teams can train more effectively.

Customer disputes

When a customer says one thing and the transaction says another, video evidence can resolve the issue quickly and professionally.
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Where AI delivers the most value in retail

AI can improve many parts of the retail experience, but a few use cases stand out because they directly affect cost, risk, and store performance.

1. Loss prevention and theft detection

Retail theft is not just a security problem. It is a margin problem. AI can help loss prevention teams spot patterns that are difficult to detect manually, including repeated behaviors, suspicious transaction sequences, and coordinated activity across stores.

This is especially useful for:

  • Organized retail theft.
  • Refund and return fraud.
  • Self-checkout theft.
  • Suspicious voids, discounts, or sweethearting patterns.

Read more about what organized retail theft is and how to fight against it

2. Operational visibility

Many store issues are not obvious until they become expensive. A missed process, a broken display, an empty shelf, or a delay at checkout can all affect sales and customer experience.

AI helps retailers catch those patterns sooner and understand where store execution is drifting from the standard.

Discover 5 ways to boost profits with AI in retail analytics

3. Self-checkout oversight

Self-checkout improves convenience, but in many cases it can also create blind spots. AI can help retailers monitor for behaviors that suggest theft, error, or misuse without requiring constant manual review.

Learn more about self checkout safety measures to take in your store

4. Analytics and trend detection

AI can help retailers move from isolated incidents to broader insight. Instead of asking only “What happened here?” leaders can ask “Where else is this happening, how often, and what should we do about it?” That makes AI useful not just for catching problems, but for shaping policy, training, staffing, and store strategy.

Grow your business with these top 20 retail video analytics use cases

How AI enhances retail security

When it comes to security, your stores are dealing with organized retail theft, self-checkout fraud, repeat offenders, internal theft, and rising expectations around employee and customer safety.

Traditional security tools still play an important role, but many retailers are discovering that simply adding more cameras or more footage does not automatically create better visibility. The challenge is not collecting more video. It is finding the moments that matter fast enough to take action.

AI helps retailers move from reactive investigations to proactive visibility. Instead of manually reviewing hours of footage after an incident occurs, AI can help surface unusual activity, prioritize high-risk events, and connect video with transaction and operational data.

For retail security teams, that creates several major advantages:

  • Faster incident investigations.
  • Better visibility into theft patterns.
  • Improved detection of repeat offenders.
  • Reduced manual video review.
  • Stronger case building with visual evidence.
  • Better coordination across multiple locations.

AI is especially valuable in environments where security teams are overwhelmed by volume. A large retailer may generate thousands of hours of video every day. AI helps narrow the focus to the events, behaviors, and exceptions that deserve immediate attention.

Discover the best AI retail security solutions to prevent loss and drive ROI

How AI helps retailers prevent theft

Retail theft continues to be one of the biggest challenges facing the industry. From organized retail theft and grab-and-run incidents to self-checkout fraud and internal theft, retailers are under constant pressure to protect margin without disrupting the customer experience.

According to the National Retail Federation, retail shrink reached nearly $113 billion in recent years, highlighting the growing financial impact of theft, fraud, and operational loss across the industry.

Modern retail theft prevention requires more than cameras alone. Retailers need visibility, context, and faster response times.

That is where AI is making a major difference. AI helps retailers identify suspicious activity faster, surface patterns that may otherwise go unnoticed, and connect incidents across multiple locations. When paired with video, AI gives teams a faster way to investigate incidents and understand exactly what happened.

AI can help retailers detect and investigate:

  • Organized retail theft
  • Self-checkout theft
  • Refund and return fraud
  • Sweethearting
  • Employee theft
  • Grab-and-run incidents
  • Suspicious transaction patterns
  • Repeat offender activity

Learn 15 effective methods to implement to prevent retail theft

What retail theft prevention devices do retailers use?

Retailers use a combination of physical security devices, video systems, and AI-driven technology to reduce theft and improve store visibility. Some of the most common retail theft prevention devices include:

  • Security cameras and video systems
  • Electronic article surveillance (eas) tags and gates
  • Smart self-checkout monitoring systems
  • Locked display cases for high-value merchandise
  • Access control systems for restricted areas
  • Panic buttons and emergency alert devices
  • AI-driven video analytics platforms
  • POS exception monitoring tools
  • Retail people counting systems
  • Motion sensors and alarm systems

While traditional theft prevention devices – like CCTV cameras for retail – still play an important role, many retailers are moving toward connected systems that combine video, transaction data, and AI-driven alerts. This gives teams more context around incidents and helps them respond faster without relying entirely on manual monitoring.

For modern retailers, the most effective approach is usually layered. Combining physical theft prevention devices with AI-driven visibility tools that help teams identify risks earlier and investigate incidents more efficiently.

Discover the top 10 retail theft prevention device solutions in 2026

The combination of AI and video creates stronger retail security workflows

Retailers are increasingly combining AI with modern retail security systems, video intelligence platforms, and connected security devices. Instead of relying only on passive video recording, AI-driven security systems help teams actively monitor store activity and respond faster when issues occur.

This creates a more proactive approach to retail theft prevention while also supporting:

  • Employee safety
  • Operational accountability
  • Compliance validation
  • Faster incident resolution
  • Better protection of high-value merchandise

For many retailers, the goal is not just catching theft after it happens. It is improving visibility across the business so risks can be identified earlier and managed more effectively.

Find out the best retail security systems to invest in for 2025

Why AI and video security is a powerful combination, for overall retail ROI (not just security)

The benefits of artificial intelligence don’t just stop at retail security solutions. One of the most practical and high-impact uses of AI in retail is artificial intelligence connected to video security to enhance operational processes.

Video gives retailers a trusted source of visual evidence. AI gives them a faster way to interpret what is happening in that video.

Together, they can help answer questions like:

  • Was that a one-off incident or part of a repeat pattern?
  • Did the transaction match what happened at the lane?
  • Was the store following the correct processes during the event?
  • Did the customer experience break down at a specific point?
  • Is the issue a training problem, an operational problem, or a theft problem?

That matters because retail teams do not just need alerts. They need context. With AI and video, retailers can move beyond guesswork and into evidence-based action. That helps teams respond faster, coach better, reduce disputes, and protect the business with more confidence.

Retail metrics AI can help improve

One of the biggest advantages of AI in retail is that it helps businesses move from reactive decision-making to measurable operational improvement. AI does not just help retailers identify problems. It helps them track patterns, measure performance, and improve key business metrics across stores.

That visibility is especially important for multi-location retailers trying to maintain consistency, protect margin, and improve customer experience at scale.

  • Shrink rate: AI helps retailers identify theft, fraud, and operational issues faster, helping reduce preventable losses.
  • Investigation time: AI-powered search and video review tools can dramatically reduce the amount of time teams spend reviewing footage and transaction data.
  • Self-checkout losses: Retailers can use AI to detect unusual self-checkout behavior and identify trends tied to theft or operational errors.
  • Queue length and wait times: AI-powered people counting and traffic analysis tools can help retailers identify bottlenecks, improve staffing decisions, and reduce customer frustration.
  • Labor efficiency: AI can help managers understand peak traffic periods, staffing needs, and workflow bottlenecks more clearly.
  • Store execution consistency: AI helps field leaders identify which locations may not be following standard operating procedures consistently.
  • Customer experience metrics: Better visibility into traffic patterns, service delays, and operational issues can help improve overall store experience.
  • Incident resolution speed: AI-driven video intelligence helps teams investigate and resolve incidents faster with clearer context and evidence.

Retailers operate on thin margins. Even small improvements in shrink reduction, labor efficiency, investigation time, or customer throughput can create meaningful business impact across dozens or hundreds of locations.

AI helps retailers make those improvements more consistently by turning store activity into measurable operational insight.

Learn the best solutions for retail people counting in 2025

How AI combined with video helps retail teams

For loss prevention teams

AI and video helps teams investigate incidents faster, identify repeat behavior, and prioritize the events that matter most when it comes to reducing loss.

  • It reduces time spent searching through footage.
  • It helps surface patterns across locations.
  • It supports stronger case building with visual evidence.

For store operations teams

AI and video gives operations leaders more clarity into store execution, whether that be improving overall profitability or enhancing the customer experience. 

  • It can reveal workflow breakdowns.
  • It helps teams validate standards.
  • It supports coaching and accountability.

For compliance teams

AI and video can support compliance validation by giving teams a reliable way to review what happened, when it happened, and whether the right process was followed. Without visibility into where compliance mistakes are occurring, fines and penalties can have a significant impact on your company’s profitability.

For field leaders and executives

AI and video helps leaders focus on what needs action now instead of relying on anecdotal reports.

  • It creates better visibility across the store network.
  • It helps prioritize attention.
  • It connects incidents to business outcomes.

How AI supports modern retail loss prevention

Loss prevention teams are being asked to do more with fewer resources while retail theft becomes more organized, more frequent, and more expensive.

AI helps modern loss prevention programs become faster, more proactive, and more scalable.

Instead of relying entirely on manual video review or store reporting, AI can help surface suspicious activity automatically, prioritize high-risk incidents, and connect video with transaction data for faster investigation.

That creates real operational value for retail loss prevention teams:

  • Faster incident review
  • Better visibility into repeat theft patterns
  • Reduced time spent searching footage
  • More efficient case building
  • Improved detection of fraud and policy violations
  • Better coordination across multiple store locations

AI is especially effective when paired with video security because it gives loss prevention teams both the alert and the visual context behind it.

AI helps retailers reduce common sources of shrink

Retail shrink can come from many different sources, including external theft, internal theft, operational mistakes, and process failures.

AI helps retailers identify patterns connected to:

  • Organized retail theft
  • self-checkout fraud
  • sweethearting
  • Refund and return fraud
  • Unauthorized discounts and voids
  • Inventory handling issues
  • Repeated operational errors

According to the National Retail Federation, the average shrink rate increased to 1.6% of retail sales in recent years, representing billions of dollars in annual losses across the industry.

Discover the 60 best loss prevention tips to follow for 2026

AI makes retail loss prevention more proactive

Traditional loss prevention strategies often rely on reacting after an incident occurs. AI changes that approach by helping teams identify risks sooner and focus attention where it matters most.

That can help retailers:

  • Improve response times
  • Focus investigations on high-risk events
  • Detect trends earlier
  • Improve store-level accountability
  • Support better staff training
  • Reduce operational blind spots

The result is a more efficient loss prevention strategy that supports both security and store performance.

Discover the 5 essential loss prevention software solutions every retailer needs

What about AI in grocery stores and other retail environments?

AI in retail is not one-size-fits-all. A grocery store has different challenges than a specialty retailer, convenience store, or big box operation. 

In grocery, for example, AI can help with:

  • Self-checkout monitoring
  • High-traffic lane visibility
  • Fresh department execution
  • Team coordination during peak periods
  • Shrink control in fast-moving environments

Other retail environments may focus more heavily on fitting room issues, high-value merchandise, customer disputes, or backroom process validation. Despite this, the common thread is the same. AI becomes more valuable when it is tied to the actual way your stores operate.

Learn 20 ways to utilize AI in the grocery store industry today

How Solink helps retailers use AI and video together for increased profitability

Solink helps retailers connect video, business data and artificial intelligence so teams can move faster, investigate more confidently, and protect margin more effectively. That means less time digging through footage and more time acting on what matters.

With Solink, retailers can support:

  • Theft detection and investigations
  • Self-checkout oversight
  • Compliance validation
  • Staff training
  • Customer dispute resolution.
  • Operational performance monitoring.

For teams trying to get more from their security infrastructure, Solink helps turn video into a practical business tool. If you are ready to see how AI-driven video intelligence can help your retail business, Solink is built to help.

Book a demo to see how Solink helps retailers turn video into actionable insights that drive profitability.
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