“We promote a culture of experimentation and a willingness to navigate uncertainty,” Royall said. “What my team has been building at the city of San Antonio is an operational process that gives the city a chance to ‘look under the hood’ of new technologies and evaluate them before we make big commitments.”
Royall has spent six years with the city, first joining as a smart city coordinator. She has a master’s degree in city planning from the Massachusetts Institute of Technology (MIT) and a bachelor’s in neurobiology from the University of Texas at Austin.
As a vocal advocate for public oversight of AI and data governance, Royall urges a more communicative relationship between vendors and the public sector.
“City governments can’t guarantee accountability for the deployment of technologies we don’t understand,” she said. “We simply need to set the bar higher in the public sector, where we are building systems that have material effects on people’s lives.”
Royall’s unique career path, from neuroscience to urban planning, was fueled by her realization that data-driven methods used to study the brain could apply to urban environments. At MIT, her thesis used predictive models to identify gentrifying neighborhoods — a precursor to today’s AI-driven city planning.
“I was able to make predictions with about 70 percent accuracy,” Royall said. “This was way before commercial AI was available, and right at the cusp of the smart city movement.”
As AI takes center stage in government, Royall underscores the importance of strong data governance.
“I think it’s important to highlight that AI is a tool, not a replacement for a human,” she said. “If a person’s job can be fully automated, employers should focus instead on expanding the role to maximize the potential of the human in it.”
This story originally appeared in the Spring 2025 issue of Government Technology magazine. Click here to view the full digital edition online.
