CES2026: White House Science Office Outlines Strategy to Win AI Race

LAS VEGAS, Jan. 7, 2026 — Michael Kratsios, director of the White House Office of Science and Technology Policy, said Wednesday that the Trump administration’s strategy to win the global artificial intelligence race centered on building domestic infrastructure, eliminating regulatory barriers, and pushing global adoption of U.S.-developed technology.

Speaking at the Consumer Electronics Show, Kratsios said the administration’s AI strategy traced back to a 2019 executive order and had since hardened around three priorities: Innovation, infrastructure, and global deployment.

On innovation, Kratsios said federal policy focused on sustaining U.S. research and development while removing regulatory obstacles that delayed commercialization. He said state-by-state AI laws created compliance costs that fell hardest on startups and small businesses, which lacked in-house legal teams and the resources to manage overlapping regulatory regimes.

Kratsios said those compliance burdens slowed market entry, discouraged investment, and favored large firms that could absorb legal costs. He said the White House was preparing a legislative proposal this year to establish a national AI framework and prevent what he described as market fragmentation caused by inconsistent state rules.

Infrastructure, Kratsios said, was now the primary constraint on AI growth. He pointed to the rapid expansion of data centers across the United States and said AI computing required electricity at a scale that local grids were not designed to support.

Kratsios said the administration had pressed companies building AI infrastructure to finance and supply their own power generation rather than draw electricity from residential and commercial grids. He added that the federal government was working to remove permitting barriers for both data centers and energy projects so construction timelines did not stall at the local level.

Kratsios said longer-term investments in advanced energy technologies, including small modular nuclear reactors and fusion research, were necessary to meet future electricity demand from AI, data center infrastructure, and additional potential technological leapfrogs.

AI workforce development also central to AI competitiveness

Kratsios said workforce development was equally central to AI competitiveness and had to begin in K-12 education. He cited an April executive order aimed at integrating AI literacy into classrooms so students understood how AI systems worked, where they could be used productively, and where they should not be relied upon.

“AI will be used in every career,” Kratsios said.

Beyond K-12 education, Kratsios said the administration was working with the Department of Labor and private-sector partners to train and reskill millions of Americans for AI-enabled jobs. He said training efforts focused on skilled trades and technical roles tied directly to data centers, energy infrastructure, advanced manufacturing, and autonomous systems.

Kratsios said companies building AI infrastructure consistently reported labor shortages as their largest operational bottleneck, often recruiting engineers and technicians nationally to staff projects.

He cited $250 million in recent federal funding for quantum computing benchmarking research, describing it as part of the administration’s effort to maintain U.S. leadership in frontier technologies.

Separately, he described a new federal technology service initiative intended to address gaps in government technical capacity by bringing private-sector engineers into short-term government roles to modernize outdated systems in federal agencies and bureaucracies.

Looking ahead, Kratsios said the administration was accelerating regulatory pathways for autonomous vehicles, drones, and AI-enabled medical devices so products that were technically viable could be legally deployed.

“The future is already here,” Kratsios said. “Our job is to make it deployable.”