Publications: Hodan Omaar

The United States plans to win the AI race by “exporting its full AI technology stack—hardware, models, software, applications, and standards—to all countries willing to join America’s AI alliance.” To succeed, it will need to pursue the right partners, make offers that meet their ambitions, and resist the urge to lead with virtue over value.

Philadelphia’s recent trash crisis highlights the need for a smarter approach to city services—one that uses low-cost AI tools to improve sanitation, reduce costs, and free up resources to better support the city’s workers.

The AI Action Plan signals that the United States is not only committed to pushing the boundaries of what AI can do but also ready to shape how it is built, deployed, and governed globally.

The American Science Acceleration Project (ASAP) is a timely effort to modernize the infrastructure that powers U.S. research. By improving how science is organized, resourced, and executed, ASAP can help unlock faster breakthroughs across a range of disciplines.

Germany’s new coalition government has created a central digital ministry to finally accelerate its slow-moving AI agenda, aiming to modernize public services and support AI innovation. But success hinges on whether it prioritizes practical reform over symbolic sovereignty, especially amid EU regulations and global competition.

The Center for Data Innovation urges the U.S. to refocus its federal AI R&D strategy on unlocking AI’s full potential by emphasizing deployment over harm prevention, linking technical design to real-world performance outcomes, and investing in the generation of high-quality, representative data to drive innovation and public benefit.

The Office of Management and Budget (OMB) issued two memos aimed at accelerating AI adoption across the federal government. But that vision won’t materialize unless other parts of the administration stop pulling in opposite directions or failing to act altogether.

U.S. AI policy prioritizes training compute while overlooking inference—the compute needed to deploy models effectively. As AI progress shifts toward optimizing inference, policymakers must adapt by supporting global deployment, refining export controls, and promoting energy-efficient AI to maintain U.S. competitiveness.

Virginia Governor Glenn Youngkin will decide on HB 2094, a flawed AI bill with inconsistent rules and unworkable enforcement. Signing it would add to a costly patchwork of state laws without improving outcomes.

The Center for Data Innovation outlined seven policy priorities we believe to be most critical for the AI Action Plan, along with specific actions the administration should take.