Every day, logistics workers face serious hazards—often with lasting consequences. These consequences affect more than employee health. Workplace injuries in logistics lead to substantial financial costs from lost productivity. Musculoskeletal disorders, forklift accidents, and vehicle collisions are among the most frequent incidents. Many serious logistics injuries result in hospitalization, underscoring how high the stakes are for frontline teams. These injuries have clear, often avoidable sources. The difficulty is catching unsafe acts and conditions before they become incidents, especially in fast-paced, high-volume settings. That’s where modern safety programs, supported by video AI, come in. When you combine proven protocols with technology that delivers real-time alerts, you can enhance safety—minimizing blind spots, and keeping your people and operations safe. In this guide, we’ll break down the top 4 frequent injuries in logistics, look at their root factors, and show how video AI can help you mitigate them.

The top 4 frequent injuries in logistics—and how video AI helps

1. Musculoskeletal disorders (MSDs) from improper lifting

Scenario:
An employee, rushed by a tight schedule, repeatedly lifts 60-lb parcels off a conveyor without assistance or proper form. By the end of the shift, they report sharp back pain—leading to lost time and a costly injury claim.

Root Causes & Impact:
MSDs are a leading cause of non-fatal logistics injuries, fueled by repetitive heavy lifting and poor ergonomics. These injuries often happen because of manual handling of heavy parcels, a lack of ergonomic assessments, and “rushing” behaviors—often incentivized by productivity targets. The resulting injury claims can be costly.

How video AI helps:
AI cameras can identify high-risk scenarios, such as a single person working in an area designated for team lifts. When this occurs, the system can flag it in real time. Supervisors can intervene to reduce risk, and the footage helps pinpoint workflow bottlenecks that lead to unsafe behaviors.

2. Forklift and powered industrial truck incidents

Scenario:
A forklift operator, rushing to keep up with outbound shipments, rounds a blind corner in a congested aisle. A pedestrian—distracted and outside the marked walkway—steps into the vehicle’s path, creating an immediate collision risk and a serious operational blind spot.

Root Causes & Impact:
Forklift incidents are a primary cause of logistics fatalities, with many involving pedestrian strikes. Blind spots, poor aisle design, and skipping seatbelt or safety protocol to “save time” are top factors. Congested aisles and inadequate separation between people and machines make matters worse.

How video intelligence helps:
Cameras equipped with AI can monitor forklift zones, detect pedestrians entering unsafe areas, and trigger timely alerts—helping reduce the risk of collisions. Video analytics can also help verify that forklifts follow designated safe paths.

3. Vehicle collisions in yard and dock operations

Scenario: A yard truck driver reverses toward the dock, struggling with low visibility and a tight schedule. A pedestrian, unseen behind the trailer, is nearly struck—a collision narrowly averted.

Root Causes & Impact: Vehicle collisions are a major contributor to trucking fatalities in logistics, with reversing and poor dock visibility being frequent culprits. Blind spots, lack of 360° camera coverage, and distracted driving—sometimes from electronic logging devices—make yard operations risky.

How video intelligence helps:
AI-powered cameras provide a comprehensive view, identifying pedestrians and vehicles as they move. The system can alert drivers and supervisors to obstruction or unsafe proximity, especially during reversing or docking. Video analytics can highlight high-risk areas by tracking frequent zone violations, guiding layout changes.

4. Struck-by and “caught-in/between” object incidents

Scenario:
A worker stacks pallets above the recommended height to maximize space. A loose box drops, striking another team member passing below. The result? A head laceration and a serious injury report.

Root Causes & Impact:
Struck-by injuries are common in high-density storage, usually from overstacked pallets or unsecured loads. Behavioral shortcuts—like skipping load securement steps—are frequent, especially during busy periods.

How video intelligence helps:
AI cameras can detect when someone enters a high-risk zone, such as an area beneath active loading, and the system can provide a quick warning. Analytics help identify team members who need additional coaching or training gaps, making follow-up efficient and targeted.

Operational hurdles and impact of the injuries

Below is a practical summary of how each injury type affects logistics operations—and how data-driven technology supports mitigation:

How technology strengthens safety in logistics

Musculoskeletal disorders (MSDs)

The safety hurdle: It’s tough to catch every risky lift—especially when workers are hustling to meet quotas.

Tech solution: AI can identify when a single person is working in an area designated for team lifts. By flagging these events, supervisors can provide on-the-spot coaching and review workflows to understand why workers might be taking shortcuts. This data helps teams identify which stations may need ergonomic redesign or mechanical lift assistance.

Forklift and powered industrial truck incidents

The safety hurdle: Forklifts and people share the same space. Blind corners, congested aisles, and shortcuts make collisions likely.

Tech solution: AI cameras monitor forklift operating zones and pedestrian walkways. If a pedestrian enters a danger zone, the system can alert supervisors. Spot AI’s Dock Safety AI actively monitors these areas and triggers alarms when pedestrians come too close to moving forklifts, helping prevent collisions and improve dock safety.

Vehicle collisions in yard and dock operations

The safety hurdle: Reversing trucks and yard vehicles often operate with poor visibility and tight deadlines, increasing the risk of pedestrian collisions.

Tech solution: Video AI maps out all movements in the yard. Pedestrians and vehicles are tracked, with automated alerts triggered when they come too close. Analytics highlight high-risk areas by tracking frequent proximity alerts or zone violations, so teams can adjust traffic flow or install physical barriers.

Struck-by and caught-in/between incidents

The safety hurdle: When loads are stacked too high or left unsecured, it’s often hard to spot the risk until something falls or shifts.

Tech solution: AI-powered cameras detect if someone enters a zone where items could fall. Footage helps with targeted coaching and retraining—closing the loop on recurring hazards.

Practical implementation of safety technology

Integrating video AI into logistics operations empowers safety teams and supervisors. Here’s how to do it right:

• Layer onto existing camera systems: Many AI platforms, including Spot AI, work with your current infrastructure—no need for a rip-and-replace.

• Sync with safety protocols: Use AI alerts to reinforce, not replace, your existing rules. For example, trigger reviews or interventions when a no-go zone violation is flagged.

• Start with high-risk zones: Focus on docks, forklift paths, and high-density storage first. Expand coverage as you see results.

• Train teams: Make sure everyone knows how AI fits in. Emphasize that it’s a tool to enhance safety and for coaching, not for disciplinary surveillance.

• Review and adjust: Use video analytics to spot repeat problems, track improvements, and inform safety meetings.

When evaluating solutions, look for platforms that are easy to search, integrate with your workflows, and provide clear findings—not just more data.

Ready to make your logistics operations safer?

Protecting your people and productivity starts with understanding your risks and taking action. See how video AI can strengthen your safety program—request a Spot AI demo to experience the platform in action.

Frequently asked questions

How can logistics companies reduce forklift and pedestrian collisions?

The most effective strategies are clear separation of pedestrian and forklift traffic, robust training, and real-time monitoring. Video AI systems provide an added layer by alerting teams when people enter forklift zones, enabling quick intervention.

How does technology help with reducing musculoskeletal injuries?

Video AI analytics can identify when single workers enter areas designated for team lifts, allowing supervisors to intervene and reinforce proper procedures. This data helps identify operational pressures that lead to unsafe behaviors.

What are the barriers to implementing AI cameras in logistics?

Typical concerns include integration with existing systems, data privacy, and ensuring alerts are useful—not just noise. It’s important to choose platforms that are easy to deploy and that support your safety goals, not create more work.

How can AI video analytics support OSHA compliance?

Video AI tools can document compliance with key OSHA standards, including forklift safety, walking-working surface requirements, and machine guarding. Video audit trails help verify that protocols are followed and provide rapid incident investigation.

Is it possible to start small and expand safety tech in stages?

Absolutely. Many logistics teams begin with high-risk areas (like docks or forklift zones), learn what works, and expand as they see benefits. Current AI platforms are designed for scalability and easy integration.

About the author

Joshua Foster is an IT Systems Engineer at Spot AI, where he focuses on designing and securing scalable enterprise networks, managing cloud-integrated infrastructure, and automating system workflows to enhance operational efficiency. He is passionate about cross-functional collaboration and takes pride in delivering robust technical solutions that empower both the Spot AI team and its customers.