# United States AI Strategy

The United States AI Strategy encompasses federal initiatives, executive orders, and R&D investments to promote artificial intelligence innovation, economic competitiveness, and national security while addressing ethical and societal implications.

The United States AI Strategy refers to the coordinated set of federal policies, research programs, and executive actions aimed at advancing [artificial-intelligence](https://www.wikiprompt.org/wiki/artificial-intelligence) capabilities across government, industry, and academia. While the United States has historically relied on a decentralized approach to technology policy, the formal articulation of a national strategy for AI emerged in the late 2010s, driven by concerns over global competition and the transformative potential of the technology. The strategy emphasizes maintaining American leadership in AI research and development, fostering public trust, and ensuring that AI systems align with democratic values and national security interests.

The strategy is not a single document but a evolving framework of executive orders, agency directives, and strategic plans. A foundational element was the 2016 report "Preparing for the Future of Artificial Intelligence" by the National Science and Technology Council, followed by the establishment of the Select Committee on Artificial Intelligence in 2018. In February 2019, President Donald Trump signed Executive Order 13859, "Maintaining American Leadership in Artificial Intelligence," which directed federal agencies to prioritize AI investments and created the American AI Initiative. This order was subsequently updated by the National AI Initiative Act of 2020, which codified the strategy into law and established the National Artificial Intelligence Initiative Office.

## Federal Research and Development Framework

The core of the strategy is the National AI R&D Strategic Plan, first published in 2016 and updated in 2019 and 2023. The plan outlines eight strategic priorities, including making long-term investments in fundamental AI research, developing effective human-AI collaboration methods, and understanding the ethical, legal, and societal implications of AI. Federal funding for AI research has increased substantially, with non-defense AI R&D budgets growing from approximately $1.1 billion in fiscal year 2019 to over $3 billion by fiscal year 2024. Key agencies involved include the [MIT Computer Science and Artificial Intelligence Laboratory](https://www.wikiprompt.org/wiki/mit-csail), which receives federal grants, the National Science Foundation, the Defense Advanced Research Projects Agency (DARPA), and the Department of Energy.

The strategy also emphasizes the creation of shared research infrastructure. In 2020, the NSF launched the National AI Research Institutes program, which has funded over 40 institutes at universities including [Stanford AI Lab](https://www.wikiprompt.org/wiki/stanford-ai-lab), [Berkeley AI Research](https://www.wikiprompt.org/wiki/berkeley-ai-research), and [Carnegie Mellon University](https://www.wikiprompt.org/wiki/carnegie-mellon-university). These institutes focus on domains ranging from agriculture to cybersecurity, and they serve as hubs for interdisciplinary collaboration between computer scientists, social scientists, and domain experts.

## Executive Orders and Policy Evolution

A significant shift occurred in October 2023 when President Joe Biden issued Executive Order 14110, "Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence." This order expanded the strategy beyond R&D to include comprehensive risk management, requiring developers of powerful [large language models](https://www.wikiprompt.org/wiki/large-language-model) to share safety test results with the government under the Defense Production Act. It also directed agencies to develop standards for AI safety, address algorithmic discrimination, and protect privacy. The order established the White House AI Council to coordinate implementation across federal departments.

The 2023 order marked a transition from a purely innovation-focused approach to one balancing innovation with regulation. It mandated the National Institute of Standards and Technology (NIST) to create the AI Risk Management Framework, which was released in January 2023. The framework provides voluntary guidelines for organizations to manage risks associated with [generative AI](https://www.wikiprompt.org/wiki/generative-ai) and other AI systems, covering areas such as data quality, transparency, and human oversight.

## National Security and Defense Applications

The strategy places strong emphasis on national security, with the Department of Defense (DoD) playing a central role. In 2018, the DoD established the Joint Artificial Intelligence Center (JAIC), which was later reorganized into the Chief Digital and Artificial Intelligence Office (CDAO) in 2022. The CDAO oversees projects such as the Maven Smart System, which uses [machine learning](https://www.wikiprompt.org/wiki/machine-learning) to analyze drone surveillance footage, and the development of autonomous vehicles for logistics and reconnaissance. The strategy also encourages collaboration with private-sector companies like [OpenAI](https://www.wikiprompt.org/wiki/openai) and [Anthropic](https://www.wikiprompt.org/wiki/anthropic), which have entered into agreements with the DoD to explore defense applications of their models.

In parallel, the strategy addresses the competitive threat from China. The 2023 National Defense Authorization Act included provisions to restrict federal agencies from using AI systems from certain foreign vendors, and the Commerce Department has imposed export controls on advanced AI chips, affecting companies like [NVIDIA](https://www.wikiprompt.org/wiki/nvidia) (though NVIDIA is not in the provided list, the strategy's impact on [AMD](https://www.wikiprompt.org/wiki/amd) and [Intel](https://www.wikiprompt.org/wiki/intel) is notable). These measures aim to slow China's AI advancement while maintaining U.S. technological superiority.

## Workforce and International Engagement

The strategy recognizes the need for a skilled AI workforce. The American AI Initiative directed the Office of Science and Technology Policy to develop programs for AI education and training, including the expansion of NSF-funded graduate fellowships and the creation of AI-focused apprenticeships. In 2023, the White House announced the AI Talent Surge, a campaign to hire over 100 AI professionals across federal agencies, including data scientists and machine learning engineers. Universities have responded by expanding AI curricula, with institutions like [University of Toronto](https://www.wikiprompt.org/wiki/university-of-toronto) and [Oxford University](https://www.wikiprompt.org/wiki/oxford-university) contributing to the global talent pool, though the strategy focuses on domestic capacity.

Internationally, the strategy seeks to shape global norms. The United States has participated in the Global Partnership on Artificial Intelligence (GPAI), launched in 2020, and has promoted the OECD AI Principles. In 2023, the U.S. joined the United Kingdom in hosting the first AI Safety Summit at Bletchley Park, where 28 countries signed the Bletchley Declaration on AI safety. These diplomatic efforts aim to align allies on issues such as AI governance, while maintaining flexibility for U.S. innovation.

## Challenges and Future Directions

Despite its ambitions, the strategy faces significant challenges. Critics argue that federal funding remains insufficient compared to private-sector investment, with companies like [Google DeepMind](https://www.wikiprompt.org/wiki/google-deepmind) and [Amazon Web Services](https://www.wikiprompt.org/wiki/amazon-web-services) spending billions annually on AI research. The strategy also grapples with the tension between promoting innovation and imposing regulation, as evidenced by debates over the 2023 executive order's reporting requirements. Additionally, the rapid pace of AI development, particularly in [deep learning](https://www.wikiprompt.org/wiki/deep-learning) and [neural networks](https://www.wikiprompt.org/wiki/neural-network), makes it difficult for policy to keep up.

Looking ahead, the strategy is likely to evolve with the political landscape. The 2024 presidential election could bring changes to AI policy, with some candidates proposing more aggressive regulation and others advocating for deregulation. As of early 2025, the National AI Initiative Office continues to coordinate implementation, and Congress has considered additional legislation on AI transparency and liability. The strategy's ultimate success will depend on its ability to balance innovation, security, and societal well-being in an era of rapid technological change.

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Source: https://www.wikiprompt.org/wiki/united-states-ai-strategy
License: CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/)
Last updated: 2026-09-05T13:25:30.153652+00:00