“As AI advances at a rapid pace, it’s imperative that we understand how to effectively integrate these technologies into our agencies to enhance efficiencies, decision-making and drive innovation,” said Clinton Bench, director of UCLA Fleet and Transit, as he moderated a webinar Wednesday for the Transportation Research Board exploring the strategic management of AI in transportation.
To position itself for a new AI age, the California Department of Transportation (Caltrans) is exploring pilot projects and use cases for AI, and policy direction. The department is near finalizing an AI strategy — and is considering establishing a “chief data and AI officer role,” a step that could be concluded in the next several months, Dara Wheeler, Caltrans division chief of research, innovation and system information said.
“Merging data and AI was purposeful when the role of the [chief data officer] CDO was crafted. It elevates the need for good authoritative and clean data before mass-scale AI efforts can be utilized,” she said. “So it was a very thoughtful and strategic decision.”
Caltrans isn’t the only state department of transportation (DOT) examining AI technologies.
Benjamin McCulloch, strategic data scientist at the Texas Department of Transportation (TxDOT), noted his agency is exploring using AI for tasks like examining bid documents. In December, TxDOT released its 2025-2027 Artificial Intelligence Strategic Plan.
And, of course, other states have hired AI leaders, or called for doing so. In January 2024, New Jersey appointed Beth Noveck, then its chief innovation officer, as its first-ever chief AI strategist. Last month, Arkansas’ AI working group recommended creating a chief AI officer position that would report to the state chief data officer. And on Thursday, the North Carolina Department of Information Technology confirmed it has hired its inaugural AI governance and policy executive, in private-sector veteran I-Sah Hsieh.
In California, Caltrans was selected to pilot two of the five original use cases for state government, around AI technologies and applications. One project focused on vulnerable roadway users safety, while another centered on traffic mobility insights. The latter, Wheeler explained, was aimed at processing “diverse data to provide traffic mobility insights.”
The vulnerable roadway users safety project “had the goal to not only capture spatial temporal dynamics of incidents, but also to uncover regional trends, and pinpoint critical hot spots,” she added. After six months of testing on each proof of concept, Caltrans is in the process of selecting a company to work on each project.
Establishing use cases for AI, understanding the technology and managing the data are all part of how transportation systems and departments will reshape themselves for the future. If civil engineers were the backbone of 20th-century transportation planning and development, watch for layers of tech expertise filling the halls of state DOTs, experts said.
“As AI adoption accelerates, agencies like DOTs will face major workforce transformations,” Patt Talvanna, partner and associate director at Boston Consulting Group, said during Wednesday’s webinar, citing a steep rise in the need for jobs in “tech roles.”
“AI and machine learning are the most in-demand skills today, and among the hardest to find,” she noted.
While some jobs will disappear, others will evolve, Wheeler said, noting the growth of new positions in areas like AI ethics, cybersecurity and the integration of AI into business processes.
“The future of AI isn’t replacing people, it’s actually empowering people to make faster, better, more informed decisions,” said Talvanna.
