Regulating AI

Artificial intelligence (AI) is advancing at a breakneck pace that experts speculate could rival previous technological revolutions like the advent of electricity. AI’s rise is already transforming the global economy. AI-related spending contributed significantly to U.S. GDP growth—accounting for over 1 percentage point of growth in 2025. Yet governments, nongovernmental organizations, and AI developers themselves have warned that, along with the many opportunities it offers, AI poses serious risks to society, politics, and national security. Consequently, policymakers are deeply engaged in discussions about how to govern AI. 

As a technology, Artificial intelligence has existed in some form for decades, but its impact on society has changed dramatically with the rise of generative AI models, such as OpenAI’s GPT, Google’s Gemini, or Anthropic’s Claude. Unlike traditional AI, which focuses on automating specific tasks or decision processes, generative AI can produce original content—text, images, audio—by learning from vast datasets. This capability enables tools that can mimic human communication, creativity, and problem-solving at scale, fundamentally shifting how people interact with technology and information. As of 2025, more than half of Americans use generative AI tools in some capacity, reflecting their rapid integration into daily life and work. 

As AI advances, its use has become increasingly widespread. The technology has propelled technological leaps, such as advances in driverless car technology or the development of new medical treatments. AI has also allowed businesses to dramatically improve their operations. Among other things, it helps banks analyze data to make trading or lending decisions and allows businesses to more precisely target advertising. The technology is able to almost entirely automate some processes, such as customer service.  

AI also has military applications, such as improving autopilot and precision targeting. Militaries are also researching lethal autonomous weapons systems (LAWS) that could make the decision to shoot or launch a missile with limited or no human intervention. LAWS could increase military power without the cost of recruiting and training more soldiers. As the technology continues to develop, its uses will also become more varied and complex. Experts predict that AI could help produce strategies to address climate change, improve healthcare processes, or facilitate breakthroughs on new technologies such as nuclear fusion.

The rapid expansion of AI offers immense societal and economic benefits. As a result, AI infrastructure investment has surged, with data center construction reaching record levels and major technology companies committing hundreds of billions of dollars to AI development.

At the same time, some policymakers worry about the implications this transformative technology has for societies. Generative AI models can influence public discourse, reshape job markets, and create content at a scale that makes it difficult to differentiate fact from fiction, and human-generated information from synthetically-produced information. The ability to generate realistic content has raised new concerns about privacy, intellectual property, and trust in information, prompting governments and businesses to reconsider regulatory priorities. AI models could also perpetuate socioeconomic and racial biases, which could have far-reaching consequences for hiring, law enforcement, healthcare, financial decision-making, and more.  

Other experts have raised concerns about how governments could use AI in harmful ways, such as through AI-enhanced facial recognition and web-tracking tools to repress their populations. In the military arena, critics warn about the ethics of employing LAWS, as they could take the decision to kill out of human hands.  

Generative AI models could also present national security risks. Governments, criminal organizations, and terrorist groups could use AI tools at relatively low cost to compromise classified information or financial systems or even assist in the creation of weapons of mass destruction.  

The strategic importance of generative AI has also altered geopolitical priorities: nations now compete to lead in AI innovation, recognizing that generative models can drive economic growth, enhance military capabilities, and shape global influence in ways that traditional AI could not. As generative AI becomes increasingly central to national security and economic competitiveness, the stakes for governance and investment continue to rise.

AI governance has evolved significantly in recent years, but governments diverge in their approaches. In the United States, the Trump administration has sought to limit AI regulation. To that end, Trump revoked previous Biden Administration executive orders aimed at mitigating the risks of AI and adopted an “AI Action Plan,” outlining policies to reduce red tape and spur innovation that would keep the United States competitive with other countries, especially China.

Many states have pushed back, enacting or proposing their own AI-safety laws, although the Trump administration has worked to limit this state-level regulation, establishing an AI Litigation Task Force to challenge state laws and conditioning some federal funding on states not enacting strict AI legislation.

The European Union has taken the most comprehensive regulatory approach to date with its 2024 AI Act, which will enter into enforcement in the Summer of 2026. The EU AI Act prohibits certain AI uses deemed unacceptable risks—including surveillance functions like building facial recognition databases or social scoring systems and establishes transparency and copyright requirements for AI models. China has also developed detailed rules governing AI, including restrictions on recommendation algorithms and AI-generated content.

At the international level, a series of AI safety summits has sought to build cooperation and shared standards. The United Nations has also launched a Global Dialogue on AI Governance, though U.S. officials have rejected international bodies asserting “centralized control” over AI policy. Despite these efforts, no binding multilateral AI regulations exist, and achieving international consensus remains challenging.

AI regulation poses several tradeoffs for policymakers. On the one hand, reducing regulatory burdens could prove essential to maintaining technological leadership in a fast-advancing and transformative field. On the other hand, it could leave people unprotected from harmful AI practices.

Those favoring stronger AI regulations also need to consider where governments should prioritize their efforts. International regulations could help establish governance at the widest scale, yet they would require lengthy negotiations and working with adversaries that may not share U.S. values on AI use. National regulations could govern some uses of AI without the need for negotiations but would have limited ability to stop AI harms that originate from outside the country.

Ultimately, the debate reflects different risk assessments. Those favoring minimal regulation emphasize AI’s economic benefits and argue that premature regulation could stifle innovation. Those favoring stronger regulation point to documented harms from AI systems, including discriminatory algorithms and privacy violations, and warn that the pace of AI development is outstripping governance frameworks. As AI becomes increasingly integrated into critical systems, the stakes of this debate continue to grow.