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2026 Motive AI Road Safety Report: Top Findings, Predictions and Risks

2026 Motive AI Road Safety Report: Top Findings, Predictions and Risks

(Image credit: Motive)


By Motive

Background
Road safety remains a critical challenge for the organizations and frontline workers who keep the physical economy and our communities running – those who stock our shelves, heat our homes, deliver essential goods, and maintain public infrastructure and safety. Across industries and the public sector alike, these teams share one thing in common: they rely on commercial vehicles to do their jobs and serve the communities that depend on them every day.

To better understand how collision patterns evolved over the past year – and where risk is headed – Motive analyzed data from commercial drivers using the Motive AI Dashcam across the United States, Mexico, and Canada.

This analysis focuses on AI-detected safety events captured in 1.2 billion hours of video to identify when, where, and why collisions occurred from 2024 to 2025. All statements included in the report are based on data captured by Motive’s platform and analyzed by our data science team, offering a data-driven look at how road safety risks shifted in 2025, what organizations can expect in 2026, and why this year represents a turning point in how collisions are prevented.


Data methodology
The 2026 Motive AI Road Safety Report is based on aggregated, anonymized insights from the Motive platform covering October 2024 through October 2025, with select analyses extending through December 2025. The report also incorporates publicly available data from the Federal Motor Carrier Safety Administration (FMCSA), the U.S. Census Bureau, and the U.S. Department of Transportation (USDOT).


Top Findings

  • Collisions are increasingly preventable. For every one collision, organizations now see seven near-collisions—early warning signals that allow intervention before damage occurs.
  • Preliminary data shows 2025 saw fewer road fatalities, but risk remains uneven and highly concentrated by time of day, season, and operating environment.
  • Late-night driving is more dangerous than rush hour. Collision risk peaks at 3 a.m., when it triples compared to midday.
  • Behavior—not road conditions or mileage—is the dominant driver of collision risk. Drowsiness, distraction, and aggressive driving consistently precede incidents.
  • Transportation and logistics fleets drive the most miles but have the lowest overall collision rates, demonstrating that the operating environment matters more than distance traveled.
  • Cell phone use is among the top five risky behaviors linked to collisions, with use peaking in late afternoons. Drivers in agriculture show the highest rates of cell phone use.
  • Smoking behind the wheel happens almost 4,000 times a day, emerging as a major and often underestimated source of distraction.
  • Even as 2025 tariff changes increased trade activity and congestion around ports and border crossings, collision rates in those areas remained stable, suggesting risk often shifts inland rather than concentrating at ports.

Top Predictions

  • 2026 will mark a tipping point where AI-powered, real-time intervention—not post-incident analysis—becomes the primary driver of collision reduction. Collision rates will still peak in Q1 due to winter weather and shorter daylight, but overall risk will continue to decline as unsafe behaviors are addressed earlier.
  • Driver behavior will remain the biggest safety risk. Drowsiness, cell phone use, and smoking will continue to outweigh road conditions as predictors of collisions.
  • Near-collisions will become the most important leading safety indicator, replacing collisions as the primary metric organizations use to manage risk.
  • Ongoing geopolitical and trade volatility will continue to shift freight patterns, pushing risk inland and into overnight corridors rather than causing nationwide spikes.
  • Industry-level safety gaps will widen. Agriculture, waste & recycling, and field services will see the biggest AI-driven safety gains as high-risk industries adopt more tailored, behavior-based safety programs.
  • One-size-fits-all safety programs will continue to underperform. Organizations will increasingly demand AI tailored to their routes, schedules, geographies, and operating environments.
  • Where and when drivers operate will matter more than how far they travel. Geography, congestion, weather, and job type will outweigh mileage as predictors of collision risk.

Traffic fatalities declined in 2025, but road risk remains
Early estimates show road safety meaningfully improved in 2025 with fewer severe collisions on the road, exactly the kind of progress AI-powered prevention is meant to drive. Severe collisions involving injuries, tow-aways and fatalities are trending 9.5% lower, with reported injuries trending 7.7% down year-over-year and focused on long-haul, heavy-duty interstate fleets that move goods nationwide. These data points concentrate mainly on the long-haul, heavy-duty transportation space, involving vehicles that see some of the greatest risk on the road due to weight and cargo.

This is also in line with what the National Highway Traffic Safety Administration (NHTSA) reported in September showing an 8.2% decrease in traffic fatalities in the first half of 2025 compared to the same period in 2024, the largest mid-year decline in more than a decade, even as Americans drove more than 12.1 billion more miles.

Our data suggests that what has changed isn’t driver behavior – it’s visibility. The decline signals that more organizations are identifying and addressing risk earlier, before collisions happen. Increased adoption of AI-powered Driver Safety products, which can detect risky behaviors and alert drivers and managers in real time, are increasingly shaping outcomes rather than simply capturing them.


To read the complete 2026 Motive AI Road Safety Report, click here.

Jan 25, 2026Dave Bean
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