Artificial intelligence (AI) is remaking transportation in ways that could reshape both economic productivity and public safety. A new study from the RAND Corporation, a American research organization known for nonpartisan policy analysis, warns that while AI promises sweeping efficiency gains, unresolved questions of safety, liability, and workforce disruption could slow the uptake of the technology.

The study describes transportation as: “poised to undergo a significant transformation driven by AI advancements. AI technologies are revolutionizing how we conceive, design, and manage transportation systems”. That transformation is already visible in freight and logistics: where autonomous trucks and driverless taxi services have been rolled out across America.

According to the study, AI systems such as adaptive cruise control and lane-keeping assistance are enhancing efficiency and safety, while traffic authorities in certain American states are using AI-powered systems to cut congestion and reduce incident detection times.

For the economy, these changes mean fewer delays, lower fuel costs, and more reliable supply chains. But they also threaten existing livelihoods. The report warns that: “such roles as bus, taxi, and truck drivers could become obsolete, necessitating reskilling programs to help these workers transition to new opportunities”.

Trust and safety risks add further complexity. The authors note that: “Automated vehicles collect vast amounts of private data, including biometric, telematic, geolocation, and video data, as well as other personal information”. This data is crucial for navigation and optimization, but it exposes passengers to cybersecurity and privacy threats that range from stalking and data leaks to insurers accessing the behavioural profiles of consumers.

Liability is another unsettled frontier. The study observes that: “Existing rules are based on the premise that a human driver is present in vehicles on the road. However, automation technology, which aims to partially or completely replace the driver, shifts the responsibility”. Without legal clarity, manufacturers, insurers, and courts face uncertainty about who is accountable when accidents occur.

The ethical dimension is equally fraught. The report highlights research showing that global preferences differ on whether AI should prioritize passengers, pedestrians, or even younger lives over older ones in unavoidable crash scenarios. Embedding those contested choices into vehicle algorithms without broad consensus risks undermining public trust.

The economic promise of AI in transport is real: faster freight, safer roads, and lower costs. But the authors argue that realizing those benefits requires policy to evolve as quickly as the technology. That means clear liability frameworks, strict privacy protections, and substantial reskilling programs for displaced workers. Absent such measures, the sector risks halting innovation amidst public distrust or pushing ahead in ways that deepen inequality and leave legal chaos in its wake.