As America’s road infrastructure continues to deteriorate, cities and states are increasingly adopting artificial intelligence to monitor roadway conditions, identify hazards, and prioritize repairs. This shift reflects a growing need for faster, more precise assessments as traditional inspection methods struggle to keep up with aging systems.

Hawaii is one of the most ambitious adopters. Through its new “Eyes on the Road” campaign, the state is distributing 1,000 AI-enabled dashboard cameras valued at $499 each. The cameras automatically inspect guardrails, signs, pavement markings, and roadway debris, distinguishing between minor damage and serious risks that require immediate maintenance. The program builds on a pilot launched in 2021, which paused due to wildfires but demonstrated strong potential. Officials believe the system can help address Hawaii’s unique logistical challenges, such as difficult terrain, limited space, and supply-chain constraints. The technology is especially valued for its guardrail-detection capabilities—an issue highlighted by a recent $3.9 million settlement after a fatal crash involving a long-unrepaired guardrail. With traffic deaths in Hawaii rising sharply in 2025, the program arrives at a critical moment.

Across the mainland, several states and cities are launching their own AI initiatives. San Jose, California, achieved a 97% accuracy rate in identifying potholes after placing cameras on street sweepers. The city is now expanding the project to parking enforcement vehicles. Mayor Matt Mahan advocates creating a shared, nationwide AI database so systems can learn from each other’s roadway images, increasing recognition accuracy and reducing the time needed to train models on rare or unusual hazards. San Jose is a founding member of the GovAI Coalition, established in 2024, which includes cities and states across the country working to share best practices and data.

Texas is undertaking one of the largest AI-driven roadway safety programs in the nation. With more lane miles than any other state, Texas integrates camera systems, mapping tools, and cellphone data collected voluntarily from participating drivers. These tools help identify outdated road signs, high-risk driving areas, and congestion patterns. AI proved particularly helpful in scanning 250,000 lane miles to locate old signs whose original installation records were on paper and nearly impossible to trace manually.

Not all AI safety innovations rely on cameras. Massachusetts-based Cambridge Mobile Telematics developed StreetVision, a system that analyzes driver behavior using smartphone sensors. By tracking events such as hard braking, the AI can pinpoint where road design or visibility issues are contributing to unsafe driving. One example occurred in Washington, D.C., where StreetVision detected widespread sudden braking. Investigators found the cause to be a bush blocking a stop sign—a simple issue resolved with basic trimming rather than complex infrastructure repairs. This illustrates how AI can reveal the root causes behind risky driving patterns and guide targeted, cost-effective interventions.

Experts view today’s initiatives as foundational steps toward an AI-enabled transportation ecosystem designed for a future with widespread autonomous vehicles. Mark Pittman, CEO of Blyncsy, predicts that within eight years nearly every new car—drivered or driverless—will come equipped with cameras. Such a landscape will require transportation agencies to build infrastructure compatible with both human and automated driving behavior. Understanding perspectives from different vehicles, whether “grandma in a Buick” or a Tesla with advanced sensors, will be essential for designing safe and efficient road systems.

Overall, AI is quickly becoming a crucial tool for monitoring America's vast and aging transportation network. By automating inspections, identifying hidden hazards, and improving decision-making, these emerging technologies promise to reshape road management and enhance public safety across the country.