White House Outlines AI Plan For Congress

White House science advisor Michael Kratsios used a national news platform to frame the Trump administration’s artificial intelligence agenda for lawmakers, focusing on jobs and future rules for the technology. Speaking on The Sunday Briefing, he outlined how the plan seeks to guide federal policy and inform Congress as it weighs next steps on AI oversight.

The appearance signaled a push to shape debate in Washington as AI tools spread across factories, offices, and schools. Kratsios, who served as the nation’s chief technology officer, said the administration’s goal was to boost research, set clear guardrails, and prepare workers for change. The message arrives as companies race to adopt AI and as public concern grows over job security and safety.

What the Administration Put Forward

“White House science advisor Michael Kratsios discusses the Trump administration’s AI plan for Congress, its potential impact on the job market and more on ‘The Sunday Briefing.’”

His remarks built on actions the White House began in 2019, when the American AI Initiative directed agencies to prioritize AI research and remove unnecessary barriers to innovation. The plan called for more open government data, better computing resources for researchers, and cooperation on technical standards. In 2020, the Office of Science and Technology Policy issued guidance urging agencies to weigh benefits and risks before writing new AI rules.

Officials also backed workforce programs to retrain employees for roles that use AI rather than replace it. The administration supported voluntary risk frameworks and international cooperation, including endorsement of the OECD AI Principles, which stress human rights, transparency, and accountability.

Jobs: Disruption and New Demand

Kratsios highlighted the debate most people care about first: work. AI is automating repetitive tasks, but it is also opening new roles in data analysis, model oversight, and maintenance. Independent studies echo this mixed picture. A 2019 Brookings analysis found about a quarter of U.S. jobs face high exposure to automation, especially in routine or predictable tasks, while many positions will change rather than vanish.

Economists say the path depends on training and the speed of adoption. If companies pair new tools with on-the-job learning, productivity gains can support higher wages and new hiring. Without training, workers can be left behind. That is why proposals to expand apprenticeships, short courses, and community college partnerships are central to any federal plan.

• Roles at higher risk: clerical work, basic data entry, routine manufacturing.
• Roles likely to grow: AI safety testing, cybersecurity, advanced manufacturing, and healthcare support.
• Key need: fast, affordable upskilling tied to employer demand.

Regulation and Safety Without Stalling Innovation

The administration’s approach asked agencies to avoid blanket bans and to target specific harms, such as bias in hiring software or unsafe uses in critical systems. This risk-based path mirrors ideas now under debate in Europe and in Congress. It leans on standards bodies and testing labs to evaluate accuracy, reliability, and security.

Kratsios pointed to the need for clear rules of the road so firms can invest with confidence. Industry groups have urged consistent definitions of “high-risk” AI and shared audit methods. Civil society groups push for transparency, contestability for people affected by automated decisions, and strong privacy protections.

Global Competition and Cooperation

AI is a strategic race as well as a shared challenge. The United States, China, and the European Union compete on research, chips, and talent. At the same time, cross-border standards and research ties help reduce safety risks. The administration’s push for allied cooperation on R&D and standards aimed to keep the U.S. at the front while aligning on values like fairness and security.

Semiconductor supply, cloud computing access, and immigration policy for skilled workers all shape national strength in AI. Congress holds key levers across each area, from funding labs to streamlining visas for graduates in science and engineering.

What Congress Could Do Next

Lawmakers are weighing bills on data privacy, transparency for automated decisions, and support for regional tech hubs. Budget choices will decide how quickly federal labs and universities can advance safe and useful AI. Targeted grants could help small businesses adopt AI responsibly, spreading gains beyond large firms.

Several steps have broad support across parties and industry:

• Increase AI R&D funding and shared computing resources for researchers.
• Set baseline transparency and testing standards for high-risk uses.
• Expand training and apprenticeships aligned with employer needs.
• Strengthen privacy rules and civil rights enforcement for automated systems.

Kratsios’s appearance marked an effort to focus the debate on growth, safety, and skills. The next phase rests with Congress, which must balance innovation with guardrails that protect workers and consumers. Watch for movement on privacy, workforce training funds, and standards for high-risk AI systems. Those choices will shape how quickly the technology delivers broad gains—and who benefits from them.