Artificial Intelligence, Particularly Generative AI, as a Broadly Applicable Technology: Impact on Productivity and Government Policies
Generative AI, a cutting-edge innovation, is poised to revolutionize productivity and potentially reshape societal and economic structures. This technology, currently under intense discussion, exhibits the three defining characteristics of general-purpose technologies: pervasiveness, continuous improvement, and innovation-spawning.
The study, which highlights the potential impact of generative AI, also warns of the rapid advancement of the technology outpacing our ability to understand and manage its implications. To mitigate potential negative consequences, the study proposes that its development should be guided by ethical principles such as transparency, accountability, and fairness.
Productivity gains from generative AI may not materialize immediately, but the evolution of earlier GPTs suggests potential for substantial improvements in the future. The study suggests that the widespread adoption of generative AI could lead to profound changes in the job market, necessitating new skill sets and potentially disrupting existing ones.
The study underscores the need for cross-disciplinary collaboration in the development and deployment of generative AI, involving experts from various fields, including computer science, economics, and sociology. It also emphasizes the need for careful consideration and regulation of generative AI to ensure its benefits are maximized while minimizing potential risks and biases.
In response, the Trump Administration's 2025 AI Action Plan outlines a comprehensive long-term policy framework to maximize AI’s productivity potential across the U.S. economy. The plan focuses on deregulation to remove barriers, infrastructure investment to support AI deployment at scale, adherence to unbiased AI principles to build trust, and strategic international cooperation.
The plan aims to remove regulatory barriers that impede AI adoption, promote open-source AI models for broader access, and invest in AI research through public-private partnerships and federal programs. It also directs agencies to repeal rules that hinder AI deployment and to exclude certain politicized topics from AI risk guidelines to foster innovation.
On infrastructure, policies emphasize streamlining federal permitting processes for data centers and energy projects critical for AI operations, aiming to overcome long-standing bureaucratic delays that limit the capacity for scaling AI systems. This includes executive orders to expedite approvals and prioritize the development of domestic semiconductor manufacturing to secure supply chains essential for AI hardware.
The policy mandates “Unbiased AI Principles” to ensure AI systems used in federal procurement are ideologically neutral and "truth-seeking," which is intended to build trustworthy AI systems and promote widespread adoption while safeguarding against misuse. Cross-sector collaboration is encouraged to integrate AI into labor, education, manufacturing, healthcare, and national security sectors for substantial productivity gains.
Moreover, the study suggests that the potential benefits of generative AI could be amplified by its integration with other emerging technologies, such as quantum computing and the Internet of Things. The full realization of generative AI's potential will require substantial investment in research and development, as well as infrastructure to support its widespread implementation.
In conclusion, the long-term policy framework designed by the 2025 AI Action Plan involves deregulation to remove barriers, infrastructure investment to support AI deployment at scale, adherence to unbiased AI principles to build trust, and strategic international cooperation—all geared toward maximizing AI’s productivity potential across the U.S. economy.
Artificial intelligence, a key component of generative AI, is attracting attention in the 2025 AI Action Plan, which aims to remove regulatory barriers and promote open-source AI models for wider access.
The potential impact of generative AI is amplified through its integration with other emerging technologies like quantum computing and the Internet of Things, requiring substantial investment in research and development.
