Each year, struck-by-object accidents cost U.S. businesses $5.55 billion across industries—and the retail sector is no exception (Source: Liberty Mutual, 2025). Retail workers face a unique combination of busy stockrooms, high-traffic sales floors, and frequent vehicle movement, all of which elevate the risk of being hit by falling merchandise, moving equipment, or shifting stock. With retail representing 12.5% of all non-fatal workplace injuries in the U.S. (Source: ElectroIQ, 2025), it’s clear that addressing struck-by-object hazards is essential for smooth operations.
But here’s the good news: most of these incidents are preventable. By combining proven safety practices with modern video intelligence, retail leaders can move from reactive investigations to proactive risk reduction. This guide breaks down the true costs, root causes, and provides a clear framework for moving from a reactive to a proactive safety model using modern technology.
Why Struck-by-Object Accidents Are a Major Challenge for Retail Operations
Unlike slips or trips, the chain reaction of a struck-by-object incident in retail can halt operations—think blocked aisles, equipment downtime, and the scramble to reassign staff. Demands for fast restocking, increased automation, and seasonal hiring spikes compound the risk. And with OSHA penalties averaging over $11,000 per incident in recent years, the need to prevent these injuries is clear.
The Top 5 Causes of Struck-by-Object Accidents in Retail—and How to Prevent Them
Understanding why these incidents happen is the first step to stopping them. Here’s a breakdown of the five leading causes in retail, with practical prevention tips and how AI-powered video analytics can take your safety program to the next level.
1. Poor Housekeeping and Cluttered Storage
The Hazard:
Picture a busy backroom during holiday season. A worker reaches for a box on an upper shelf, but stacked merchandise teeters dangerously nearby. Seconds later, a stack of unbalanced boxes tumbles, striking the worker on the arm. These scenarios play out daily when aisles are cluttered or storage racks are overfilled.
Traditional Prevention:
Enforce “clear aisle” policies and regular housekeeping checks.
Store heavier items on lower shelves and avoid overhanging stock.
Schedule routine inspections for shelf stability and organization.
How AI Amplifies Prevention:
Video analytics can flag crowding, clutter, or blocked walkways in real time. When a stockroom gets too congested, the system can surface alerts so teams can clear hazards before anyone gets hurt. Over time, insights from flagged footage help pinpoint recurring trouble spots, making daily housekeeping more targeted and effective.
2. Vehicle and Forklift Movement in Stockrooms
The Hazard:
A team member is moving inventory with a pallet jack while another employee, focused on shelf stocking, steps into the path of a reversing forklift. A near miss is averted this time, but in many cases, poor visibility or miscommunication results in a struck-by-vehicle injury.
Traditional Prevention:
Strict operator training and certification for forklifts and pallet jacks.
Clear marking of pedestrian and vehicle pathways.
Scheduled maintenance and routine safety checks of all equipment.
How AI Amplifies Prevention:
AI video can detect when forklifts or other vehicles enter “no-go” pedestrian zones, instantly flagging unsafe movements. Systems can also surface near-miss events, giving safety managers hard data to update traffic routes or retrain staff—no more waiting for someone to report an incident.
3. Improper Material Handling and Stacking
The Hazard:
A new employee, eager to finish restocking, piles products precariously high on a cart. As the cart turns a corner, a box slides off and strikes a coworker in the leg. Many struck-by injuries stem from improper stacking or hurried, unbalanced loads.
Traditional Prevention:
Training for safe lifting, stacking, and transport procedures.
Pre-shift checks for unstable loads or damaged shelving.
Use of anti-tip brackets or barriers for high shelves.
How AI Amplifies Prevention:
Video analytics can monitor for “person enters no-go zones” and spot unsafe stacking or handling behavior. When risky behavior is detected—like running with a loaded cart or entering a restricted area—the system surfaces these events, prompting coaching or policy adjustments before an accident happens.
4. Equipment Failures and Lack of Maintenance
The Hazard:
A food retail employee uses a slicer that’s overdue for maintenance. The machine jams, and as the worker tries to dislodge the product, a loose part snaps off, causing a hand injury. Equipment malfunctions, especially in busy environments, are a major source of struck-by-object injuries.
Traditional Prevention:
Scheduled preventive maintenance for all equipment (e.g., forklifts, slicers).
Lockout/tagout procedures during repairs.
Routine inspections and immediate removal of faulty equipment.
How AI Amplifies Prevention:
AI video can monitor for “unattended workstation” or “vehicle absent” events, signaling possible equipment abandonment or malfunction. Real-time alerts help ensure that machines in need of service are identified quickly, reducing the risk of injury from unexpected failures.
5. Behavioral Risks: Rushing, Distraction, and Ignoring Protocols
The Hazard:
During peak hours, staff rush to restock shelves and serve customers. In one scenario, an employee multitasking with a handheld device walks directly into a stack of merchandise being moved by a coworker. Distraction and rushing undermine even the best safety protocols.
Traditional Prevention:
Regular safety briefings and signage reinforcing “no running” and “stay alert” rules.
Task rotation to reduce fatigue and maintain focus.
Incident reporting and review to identify behavioral trends.
How AI Amplifies Prevention:
Systems can flag “running” or “possible fall” events, both of which are proxies for rushed or distracted behavior. Reviewing these alerts helps managers identify high-risk times (such as shift changes or restocking rushes) and target training or staffing adjustments accordingly.
Integrating a Modern AI Camera System: From NVR to AI Insights in Retail
Adopting new safety tech doesn’t mean ripping out your existing cameras. Today’s AI-powered video platforms are built to work with the cameras you already have—including most POE models. Here’s how a cloud-native approach transforms your safety program:
Feature | Traditional NVR | Modern AI Camera Platform |
|---|---|---|
Camera Compatibility | Often requires upgrades | Works with most existing cameras |
Storage | On-prem hardware | Secure, cloud-native, scalable |
Maintenance | On-site, frequent | Minimal, remote updates |
User Access | Limited seats | Unlimited users, unified dashboard |
Video Review | Manual, time-consuming | AI-powered search & detection |
Actionable Insights | Passive footage | Real-time safety alerts |
A modern AI system acts as a smart layer that bridges your on-prem cameras to a secure, cloud-native dashboard. No more bulky servers or endless footage review. Real-time AI analysis surfaces critical safety events—like forklifts in pedestrian areas, running in aisles, or crowding—so you can act before a minor hazard becomes a major incident.
Camera Compatibility Tip: You don’t need a full “rip-and-replace.” These platforms are designed to work with most legacy and modern POE cameras.
Integration Best Practices:
Align new video tools with your existing safety policies and OSHA 29 CFR 1910.22/1910.176 requirements.
Run a risk assessment: Map high-risk areas in your store or DC and ensure camera coverage matches hazard zones.
Choose systems that support unlimited user access—so safety isn’t siloed in one department.
Use insights from video analytics to inform regular safety huddles, incident reviews, and staff training.
Transform Retail Safety—Book a Safety Consultation
Every struck-by-object incident is a chance to improve—not just to react. By combining proven safety practices with AI-powered video analytics, retail leaders can cut risk, speed up investigations, and build a safety culture that supports every team member.
Ready to see how proactive video intelligence can empower your retail safety team? Book a consultation with Spot AI’s experts and get tailored, actionable guidance for your operation.
Frequently asked questions
What are the most common causes of struck-by-object injuries in retail?
The most common causes include poor housekeeping, cluttered storage, equipment failures, unsafe vehicle movement, and behavioral risks like rushing or distraction (Source: OSHA, 2025).
How can retail organizations implement safety technology without disrupting operations?
Modern AI video platforms overlay analytics on your existing camera feeds. This means no major installation downtime, and they automate hazard detection and reporting—supporting your staff rather than replacing them.
What OSHA regulations apply to struck-by-object prevention in retail?
OSHA 29 CFR 1910.22 requires clear aisles and workspaces, while 1910.176 covers safe material handling and storage. Regular training, inspections, and equipment maintenance are also required (Source: OSHA, 2025).
What practical steps should retail leaders take before adopting AI camera technology?
Start with a safety risk assessment, identify high-traffic and high-risk zones, and review your current camera coverage. Involve IT and safety teams early. Pilot the system in one area, learn from the data, and then expand.
How does AI video analytics support incident investigations?
AI-powered platforms automatically flag relevant events—such as near-misses or unauthorized entries—making it easier to review footage, understand root causes, and support faster, more accurate investigations for compliance.
How can safety technology help reduce stress for safety managers?
AI-driven analytics automate much of the manual monitoring and reporting, freeing safety managers to focus on proactive planning and team support—rather than reacting to every incident.
About the author
Joshua Foster, IT Specialist, Spot AI
Joshua Foster is an IT Specialist at Spot AI with hands-on experience in deploying, maintaining, and troubleshooting security camera systems for enterprise environments. He is passionate about helping businesses optimize their video surveillance for maximum uptime, safety, and operational insight.
