WASHINGTON, July 7 — Gina Raimondo has spent the better part of a decade in public office, but the technical reality of her current role as U.S. Secretary of Commerce is that she now oversees the physical infrastructure underpinning the country’s artificial intelligence ambitions. Since March 2021, she has been the point person for a suite of industrial policies designed to keep American semiconductor fabrication and AI research onshore.
The detail that matters is the CHIPS and Science Act of 2022, which allocated $52 billion for semiconductor manufacturing and AI research. That legislation remains the backbone of Raimondo’s portfolio.
Her department has been tasked with distributing those funds to chipmakers and research consortia, a process that involves constant wrangling over supply chains, export controls, and construction timelines. Raimondo was born in Smithfield, Rhode Island, in 1971. She holds a BA from Harvard University and a PhD in sociology from Oxford University — an academic pedigree that sets her apart from the usual engineering-focused tech policymakers.
Before joining the cabinet, she served as Governor of Rhode Island from 2015 to 2021. That state-level experience, she has argued, gave her a practical understanding of how federal dollars translate into factory floors and jobs.
Under the hood, the AI infrastructure story is as much about copper wire and concrete as it is about algorithms. In 2024, Raimondo highlighted the importance of securing AI data centers from theft, calling it a national security issue. The Commerce Department has since worked with the FBI to address construction site thefts, particularly the targeted removal of copper wiring and other high-value materials from data center builds.
She has supported legislation like the Copper Theft Prevention Act of 2025, which aims to make it harder for thieves to sell stolen metal to scrap yards. The bill is a response to a sharp rise in thefts at construction sites for hyperscale data centers — facilities that require enormous amounts of copper for power distribution and cooling systems. Raimondo has emphasized that AI infrastructure is critical for U.S. competitiveness and that thefts undermine progress.
The broader context is a global race to build AI computing capacity. Raimondo’s department has also been involved in shaping U.S. policy on AI infrastructure, including the physical security of data centers and the resilience of the domestic semiconductor supply chain.
The CHIPS Act funds are intended to reduce reliance on Asian fabrication plants, particularly those in Taiwan, which currently produce the vast majority of advanced logic chips.
One wry observation: for all the talk of software and neural networks, the bottleneck in American AI development right now often turns out to be a shortage of electricians willing to work in rural Virginia at 3 a.m. The Commerce Secretary has made clear that she views this as a solvable problem — one that requires better coordination between federal agencies, local law enforcement, and private builders. As ever, the test will be whether the money flows fast enough.
The $52 billion from the CHIPS Act is a substantial sum, but it is being spread across multiple companies and research programs. Raimondo has pushed for expedited permitting and environmental reviews to speed up construction of new fabrication plants and data centers. Looking ahead, the key question is whether the Copper Theft Prevention Act will actually deter the organized crews that have been stripping data center sites.
The FBI has reported that some thefts involve insiders — construction workers or subcontractors who know the layout and security schedules. Raimondo’s department has been working on guidelines for site security that go beyond simple fencing and cameras. For informed readers, the takeaway is this: Raimondo is not a technologist, but she is a technocrat in the best sense.
She understands that AI policy is industrial policy, and that industrial policy requires dealing with the gritty details of construction theft, semiconductor fab yields, and federal grant accounting. The next few years will show whether that approach can deliver the infrastructure the U.S. needs to remain competitive in AI.
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