AI Accelerating Move to Modernize State Agencies, Say State CIOs

“The Explosion of GenAI onto the scene has accelerated the desire of agencies to modernize and to do so quickly,” said Amanda Crawford, CIO, State of Texas, at a recent technology summit. Other featured panelists at the StateScoop virtual session, Where AI and IT Modernization Collide, included Montana CIO Kevin Gilbertson and Massachusetts CIO Jason Snyder.   At the IT Modernization & AI Summit 2024 on November 12, Crawford said Texas made “significant strides” in data governance and data quality—all crucial to AI. She explained that Texas uses data management officers, who participate in a data management advisory committee, to improve data quality and data management. That committee also suggests changes to the legislature on state law to advance important data issues.

Report: Access to Care Grows after Medical Licensure Compact

A research paper that analyzed data from the Interstate Medical Licensure Compact concluded that both access to care and physician-practice grew after the compact. The economics paper pointed to state-specific physician licensing decreasing patient access to care in underserved area. The authors of Access to Care and Physician-Practice Growth after the Interstate Medical Licensure Compact suggest that state licensure compacts, like the medical compact, aid workforce mobility—including the mobility to underserved area with few physicians.

AI Hurdles, Risks and Readiness in State Government

A survey of 1,000 CIOs/CTOs reveals the challenges and readiness of AI across sectors, including in state and local government. In the 2024 AI Readiness Report: Greatest Risks and Ways to Avoid Them only 17% of those from the state and local government sector view AI as essential for a competitive advantage versus 47% in the financial sector, for example. For using AI for data analysis, again state and local government reported the lowest use, as compared to financial services and the healthcare industry. The report explains that “in contrast, state and local governments are adopting AI more slowly. They may be facing budget constraints or legacy systems, which hinder their ability to fully implement AI.”

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