By: Maya Zuk, Policy Associate, Policy Strategy, SAFE
Artificial intelligence (AI) is emerging as a key front for global influence, and nations are racing to shape the standards governing the technology’s use, hoping to lead in the next era of AI—deployment.
AI-enabled technologies present vast benefits, particularly in the physical realm—with innovations applying to defense readiness systems and transportation logistics alike. ReMo’s upcoming report, AI in Motion: Securing America’s Edge in Safer, Smarter Transportation, highlights these benefits and the technology’s ability to offer generational opportunities to save lives, improve efficiency, and build better transportation systems.
But the nation also faces a stark warning. While the U.S. has historically led in AI innovation, a range of barriers could hold back deployment—potentially ceding global leadership to China, which is intensifying its push into global AI governance, standard-setting, and deployment.
This would be more than a missed commercial opportunity… it’s about global safety, privacy, and rules of the road.
So far, U.S. federal agencies have slow-played AI deployment and governance. The AI Action Plan released in July helped build policy momentum, but China released its own counterpart strategy days after the U.S.
Meanwhile, per ReMo’s report, the Department of Transportation has only recently incorporated AI into its regulatory actions. It and other U.S. government agencies remain behind Chinese counterparts in setting AI deployment policy.
As the U.S. seeks to counter China’s aggressive actions, it will face significant challenges. Ensuring energy infrastructure resilience, rectifying America’s current regulatory fragmentation, and engaging with other nations in global standards-making will be necessary.
Competing Visions
The U.S. and China’s approaches to AI-enabled technologies reflect their differing governance values. The U.S. approach relies on rapid innovation through deregulation, private-sector leadership, and the export of customizable AI systems to allies. China’s strategy positions AI as a global public good, driven by state-backed development, centralized data, and government-driven deployment. Beijing’s Global AI Governance Action Plan is framed around multilateral cooperation and inclusive access.
The PRC’s AI plan presents itself as cooperative and inclusive, emphasizing support for AI development in the Global South and a stated respect for national sovereignty and developmental differences. However, this rhetoric often clashes with the reality of domestic laws and enforcement. The plan is built upon the Chinese Cybersecurity Law, which grants the government access to all information collected through cyberspace by Chinese-based firms, and its widespread surveillance infrastructure, assuring that AI development aligns with Chinese national priorities.
The PRC has tightened its grip over AI development through strict content regulations that censor chatbot responses and align them with state-approved narratives. Combined with facial recognition systems that track dissidents and expansive monitoring capabilities, these measures reinforce its model of state-directed technological governance. This approach not only exports Chinese technologies but also embeds its values as part of the default standards of global AI systems.
While both countries see public confidence as crucial, their approaches differ sharply: developers in the United States rely on safety validation to win acceptance, whereas China’s model limits public scrutiny of AI performance and safety issues.
Transportation: A Strategic Front
Transportation is one of the most visible and high-stakes domains for AI competition. Beyond the convenience of automating, dramatically speeding, and potentially improving the accuracy of tasks once done by people, AI in mobility can reduce traffic fatalities, cut costs, and improve transportation access throughout the world. Progress on these markers is highlighted through case studies in ReMo’s AI in Motion report.
In the United States, companies like Waymo are operating autonomous ride-hailing services in an ever-expanding list of cities, while Aurora is testing self-driving freight trucks across Texas highways, with both companies emphasizing the safety applications of their technologies. Waymo, for example, has reduced third-party bodily injury claims by 92 percent in comparison to the overall driving population. As global competition intensifies, deploying trustworthy, high-quality transportation AI is key to securing both public trust and international leadership.
China, meanwhile, is moving quickly to dominate this space. It is aggressively deploying embodied AI, or systems integrated into physical platforms like autonomous vehicles, in markets such as Europe and the Middle East. These deployments not only export technology but also China’s regulatory values. In embodied AI, technical standards become strategic leverage: the first systems to take root in global markets often define safety protocols, data governance, and the values embedded in infrastructure.
China’s government-backed, open-source AI model allows companies to develop adaptable technology without the need for immediate commercial returns. Local governments are investing heavily. Wuhan alone has committed $2.3 billion to smart transportation projects within the city. In contrast, U.S. firms face soaring development costs, with supercomputer hardware prices doubling each year, possibly reaching $200 billion in 2030.
To stay competitive, American firms must drive down costs by establishing regulatory sandboxes—controlled, temporary frameworks that allow companies to pilot autonomous vehicles and other AI-enabled transportation systems on public roads under streamlined oversight. Such sandboxes allow for rapid deployment and testing, and rapid deployment can be achieved by speeding up infrastructure buildouts for data centers and energy supply. Success will depend on making AI a competition of quality, not cost, leveraging commercial deployments to fund innovation and maintain leadership.
Standards and Strategy
While U.S. companies race to deploy, China is pairing rapid deployment with a strategic push to shape global standards, leveraging its growing presence in international standard-setting bodies and its perceived leadership in AI research. A key part of this strategy is its aggressive patent activity, now leading the world with more than 170,000 patents across all AI fields. These filings not only reflect domestic innovation but also serve as a tool to influence technical standards and secure long-term competitive advantages.
To counter this, the United States must respond with a coordinated diplomatic and commercial strategy, prioritizing the global deployment of trustworthy, American-developed AI systems. Without swift action, the United States risks ceding influence over the foundational rules that will govern 21st-century technology and society ReMo’s AI in Motion report elaborates on principles for policymakers on developing standards that support U.S. leadership.
Trust: America’s Strategic Advantage
Public trust is the United States’ greatest asset in the global AI race. American developers of autonomous vehicles are focused on transparency and safety, publishing detailed safety reports, engaging with regulators, and conducting public trials to build confidence in their technologies. While safety incidents involving U.S. autonomous systems have occurred, developers take accountability and strive to earn the public trust. This ethos builds trust, and that trust opens markets.
This openness is harder to find in China, where safety concerns may be censored. China’s top-down, opaque approach and lack of privacy protections has not restricted uptake of Chinese technology in countries around the world, essentially exporting and promoting an unsafe global transportation system. The United States not only risks falling behind in international deployments, but could lose a larger battle for values and governance that prioritizes safety and consumer protections.
Around the world, Chinese technology has already supplanted electric vehicle manufacturing and innovation. European automakers cannot compete with the standards Chinese manufacturers have set, nor can they compete on costs. The logical next step for Chinese developers is AV technology, combining their expertise in auto manufacturing with their growing emphasis on AI development and deployment.
The stakes are clear: Setting global standards will not only shape the future of AI but the principles embedded in its use. Chinese transportation AI exports bring governance models that emphasize centralized control and broad state access to data. For the United States, that raises concerns about privacy, transparency, and market openness in the global transportation system. The White House’s AI Action Plan outlines steps to address these risks, from accelerating deployment and streamlining regulatory approvals to expanding exports of trustworthy, safety-focused AI technologies.
The race to define global AI standards is not just about technology—it is about the values we embed in the systems that will shape everyday life. Numerous principles offered in AI in Motion can offer the nation a path forward, overcoming strategic challenges and ensuring continued U.S. competitiveness and leadership in AI. To lead, the United States must act swiftly and wisely, matching innovation with integrity, trust, and deployment.
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