Thought for 6 seconds

Over the past two decades, machine learning—the leading branch of artificial intelligence—has risen rapidly on the strength of exploding data volumes, cheaper storage and computation, and continual algorithmic breakthroughs. Deep-learning techniques and generative AI systems such as ChatGPT are now transforming day-to-day business practices. Yet state and local transportation agencies are drowning in new data streams faster than they can translate them into actionable insight. TRB’s NCHRP Research Report 1122, *Implementing Machine Learning at State Departments of Transportation: A Guide*, equips DOTs with a primer on promising ML use cases, tools for weighing costs, benefits, risks, and constraints, and a roadmap for fostering the data-driven culture needed to scale these capabilities across transportation programs.