The United States stands at a pivotal moment as a new presidency begins, offering what many describe as a golden opportunity to leverage artificial intelligence as a transformative driver of economic growth, national competitiveness, and global leadership. This extensive vision, articulated by Brad Smith, Vice Chair and President of Microsoft, frames a three-part strategy: to advance world-class American AI technology and infrastructure; to champion broad AI skilling that unlocks career opportunities across the economy; and to accelerate the export of American AI capabilities to allies, strengthening domestic strength while ensuring benefits are shared globally. The emphasis is on building a durable foundation that can sustain the nation’s economic vitality for decades, anchored by collaboration among government, industry, academia, and the nonprofit sector. The challenge—and the opportunity—will be to implement these principles in a way that brings together diverse stakeholders, aligns public policy with private innovation, and fosters an ecosystem where AI can deliver broad-based prosperity.
Technology as a foundation for economic growth
Across history, major industrial revolutions have redefined the contours of economic performance, driven by breakthroughs in technology that unlock new productivity frontiers. The first industrial revolution, sparked by the steam engine and enriched by advances in ironworking, transformed production processes and trade in the United Kingdom, catalyzing widespread economic expansion. The second industrial revolution, which emerged in the late 19th century, saw electricity become the energy and signaling backbone of the American economy, enabling a manufacturing renaissance by enhancing machine tooling and enabling scale in production. The third industrial revolution, unfolding in the latter half of the 20th century, was propelled by computer chips and software, with the United States once again at the forefront of this new technological era, nurturing new companies and reshaping entire industries, among them entities that would cultivate a software-driven economy.
These eras share a common thread: they were all marked by the emergence of General-Purpose Technologies, or GPTs. Unlike products designed for a narrow purpose, GPTs spark widespread innovation and productivity gains by enabling a broad set of new capabilities across sectors. Ironworking, electricity, advanced machine tooling, computer chips, and software rank among history’s most influential GPTs, continually altering what is possible in business and government. Today, artificial intelligence is widely recognized as another GPT, with the potential to catalyze innovation, accelerate productivity, and redefine economic opportunity across almost every domain. This perspective underpins the argument that the next four years could establish a solid, enduring foundation for American economic success across the economy and the workforce.
The opportunity to act decisively rests on a robust infrastructure for AI—one that supports rapid research, scale-up, experimentation, and deployment. An infrastructure-led approach is essential because the speed with which AI capabilities can be trained, tested, and applied directly influences how quickly businesses can realize productivity gains and how swiftly workers can acquire new competencies. This requires not only hardware and data resources but also the software ecosystems, open-source communities, and the talent pipelines that make AI usable and trustworthy. The United States has a unique advantage here: a private-sector-led ecosystem anchored by dynamic startups, established technology giants, and a broad base of software developers and systems integrators who constantly push the frontiers of what AI can do. The enduring question is how to sustain and expand this advantage in a manner that aligns incentives, protects security and privacy, and fosters inclusive growth.
The private sector’s leadership has always defined American AI momentum. Today, the United States remains at the apex of the global AI race thanks to the scale of private capital, the ingenuity of American companies of every size, and a thriving landscape that supports experimentation, risk-taking, and rapid iteration. Microsoft’s experience, including its long-standing partnership with OpenAI and collaborations with a new generation of AI challengers and collaborators such as Anthropic and xAI, illustrates how the private sector can drive rapid advances in AI models and applications. Across the economy, a wave of AI startups and established firms is moving from GPUs to AI accelerators with tensor-based architectures, enabling faster training and more efficient deployment. Software is increasingly being redesigned as AI-enabled applications, integrating intelligent capabilities into everyday workflows and decision-making processes.
Yet, no one sector can sustain this momentum alone. The essential foundation for AI innovation is a broad, competitive ecosystem that includes open-source software, chip suppliers, system integrators, service providers, and countless software developers who tailor AI solutions to meet customer needs. The scale of the infrastructure required to train and deploy AI models—thousands of AI-enabled data centers around the world—depends on a complex supply chain of construction firms, manufacturers, and skilled professionals across trades. Electricians, pipefitters, and other skilled laborers are indispensable to building and maintaining the energy-efficient facilities that host AI workloads. The success of the AI era thus rests on the seamless coordination of diverse players and the creation of an environment in which competition, collaboration, and innovation can flourish together.
Since World War II, American innovation has depended on two interlocking pillars: sustained support for basic research and a vigorous private-sector commitment to product development. Basic research—often funded at universities through federal programs such as the National Science Foundation and other agencies—drives the curiosity-driven discoveries that lead to transformative breakthroughs. The public sector thus plays a crucial role in nurturing the foundational science that later becomes the core of commercial applications. At the same time, American industry has mastered the art of translating those ideas into practical products and services, moving new knowledge from laboratory benches to the broader market with speed and efficiency. The synergy between fundamental research and applied development has long distinguished the United States as a leader in innovation, ensuring that public investment in knowledge translates into robust private-sector activity.
There is a pressing imperative to strengthen these foundational elements as part of the incoming administration’s agenda. Building on the policy blueprint laid during President Trump’s first term, there is a case for expanding investments in basic research and expanding opportunities for universities and researchers to push the frontiers of AI. An enhanced emphasis on basic research complements a continued commitment to product development and commercialization, enabling a sustainable pipeline that feeds both discovery and practical impact. The path forward includes channeling more resources into basic research at universities and federal agencies while sustaining robust support for the translation of those discoveries into market-ready AI products and services. Such a dual track helps maintain a steady cadence of innovation, ensuring that America remains at the cutting edge of AI capabilities and that the benefits of this progress are broadly shared.
In this context, AI skilling—creating an expansive, accessible pipeline of AI talent—emerges as a central component of the technology foundation. The ability to attract, train, and retain AI-skilled workers across industries is essential to ensuring that technology translates into real economic value and improved livelihoods. A national AI talent strategy should focus on equipping workers of all ages and backgrounds with the competencies needed to participate in the AI-enabled economy. This involves not only technical training for software engineers and data scientists but also roles in design, integration, governance, security, and operations that empower organizations to implement AI responsibly and effectively. The cross-cutting nature of AI means that almost every sector—from manufacturing and agriculture to health care, logistics, and public administration—needs people who can apply AI tools to real-world problems.
The fundamental objective, therefore, is to foster a broad ecosystem of learning and opportunity. This includes on-the-job training and apprenticeships, online platforms, and formal education pathways—from community colleges and vocational programs to four-year institutions and advanced research centers. It also involves partnerships with non-profit organizations, industry groups, and public agencies to reach underserved populations and rural communities, ensuring that AI opportunities are accessible across the country. In the years ahead, the health of the AI ecosystem will depend on how effectively these partnerships are cultivated and how well they align incentives across sectors. A well-designed talent strategy will not only prepare the current workforce but also lay the groundwork for the next generation of AI professionals, enabling millions of Americans to participate in the AI economy and benefit from higher-paying, more productive work.
The role of community colleges, in particular, emerges as a pivotal piece of the AI skilling puzzle. Across the United States, these institutions serve as critical entry points for workforce development, offering affordable, accessible, and flexible education that can adapt quickly to evolving industry needs. Partnerships with national initiatives, such as the National AI Consortium for Community Colleges, help align curricula with industry demand and facilitate practical training that leads to employment. Through programs like AI Bootcamps, faculty training, and collaboration with workforce agencies, community colleges are preparing students for in-demand AI roles and helping workers upskill mid-career. This approach broadens the reach of AI training to diverse populations and geographies, including rural areas where access to high-quality education can be a challenge.
Microsoft’s broader skilling initiatives provide a concrete example of the scale and scope of this effort. In 2025, the company is aiming to train 2.5 million American students, workers, and community members in AI skills that can translate into new jobs, career advancement, and entrepreneurial activity. The goal is to reach every corner of the country, bringing AI fluency to a wide audience and enabling individuals to leverage AI tools in their current roles or to transition into new AI-enabled careers. A central element of this strategy is a national effort to deliver AI training that is practical, regionally relevant, and aligned with real-world needs. This entails developing curricula that cover foundational AI concepts, software engineering practices, data ethics, and the governance frameworks necessary to deploy AI responsibly in organizations across public and private sectors.
A major focus area is the collaboration with community colleges to scale AI education nationwide. The National AI Consortium for Community Colleges serves to provide industry-relevant AI curricula, while AI Bootcamps help prepare educators to deliver cutting-edge instruction. This approach ensures that teachers and administrators have the competencies to guide students and workers through AI-enabled learning pathways. In addition to curricular improvements, there is a push to integrate AI into K-12 and higher education in meaningful ways that prepare students for the jobs of the future. The aim is to create a continuum of AI literacy that begins with early exposure and extends through higher education and lifelong learning, enabling individuals to adapt to the changing demands of the labor market.
Beyond formal education, the AI skilling agenda emphasizes practical, experiential learning that connects students with real-world opportunities. Programs like the Microsoft Copilot for Career Navigators illustrate how technology-assisted guidance can support communities in navigating the AI-driven economy. By equipping career navigators with AI-enabled tools, educators and workforce professionals can provide targeted advice, identify training pathways, and connect learners to relevant opportunities. The objective is to ensure that AI education translates into tangible outcomes—jobs, internships, apprenticeships, and long-term career growth—across diverse populations and regions.
Efforts to broaden AI training also target non-traditional learners, including high school graduates and individuals with limited post-secondary education, who may encounter barriers to higher education. AI has the potential to help close the income gap by enabling more inclusive pathways to high-wage, AI-enabled jobs. Initiatives like the National 4-H AI Skills Partnership, which leverages Minecraft Education to foster AI fluency among 1.4 million youth, and FarmBeats for Students, in partnership with the Future Farmers of America, demonstrate how AI can be embedded in practical, hands-on learning experiences. These programs show how AI concepts can be introduced early and how technology can be used in fields such as agriculture to enhance productivity and sustainability.
The central takeaway from Microsoft’s ongoing skilling work is clear: AI represents not only a set of new tools for work but also a powerful catalyst for learning across the entire education-to-employment pipeline. The nation has a rare chance to set a national north star that makes AI skills accessible and meaningful for all Americans. But achieving this requires an expansive network of partnerships across jurisdictions, sectors, and communities. The ultimate objective is to ensure that every American can develop AI fluency—enabling them to apply AI in their jobs much as they currently use laptops, smartphones, and the internet—and to prepare the country for what could be a transformative era in work, productivity, and opportunity.
Within this evolving landscape, a recurring insight emerges: the United States has a historic role in creating knowledge workers who power the modern services economy. The broad success of AI skilling will depend on expanding the reach of AI literacy and capability far beyond a small cadre of specialists. The aim is to multiply the number of AI-proficient workers who can contribute to the economy in meaningful ways, extending well beyond software development to include manufacturing, logistics, agriculture, education, government, and the broader public sector. In the coming decades, the aspiration is to enable millions of AI-enabled jobs that extend across multiple sectors and geographies, shaping a future in which AI augments human capability rather than replacing it.
This vision implies that some individuals will require deeper, more specialized training. For many people, training will occur on the job or through online platforms such as LinkedIn Learning, complemented by local community colleges or four-year universities. For others, training will build on existing disciplines in computer science or data science and may evolve into a next generation of AI engineering. Still others will pursue business-oriented learning to help design or manage AI integrations within enterprise processes across private, public, and nonprofit sectors. The goal is a broad, adaptable skill set that suits diverse career trajectories while enabling the adoption of AI tools in practical settings.
In parallel, the private sector is playing a critical role by scaling training efforts and expanding access to AI knowledge. The collaboration between Microsoft and partners demonstrates how the private sector can complement public education and workforce development initiatives. The company’s commitment to training millions of people reflects a belief that AI skilling should be a shared national priority. The broader ecosystem includes industry associations, universities, community organizations, and government programs that collectively expand opportunities for workers to gain hands-on experience with AI and to develop the competencies that employers seek. This multi-faceted approach helps ensure that AI skilling is responsive to local needs and capable of delivering tangible economic benefits across communities, from urban centers to rural regions.
As this approach unfolds, one conclusion becomes evident: AI has the power to democratize access to high-quality, high-paying work. By lowering barriers to entry for many professions, automating rote tasks, and amplifying human creativity, AI can broaden participation in the future economy. It can enable entrepreneurs to launch new businesses, create new jobs, and unlock productivity gains across sectors. The technology also has a potential to reduce economic inequality by offering opportunity to individuals who might not have pursued traditional post-secondary education. Harnessing this potential will require clear national direction, sustained investment, and a commitment to building an inclusive AI workforce that reflects the country’s diverse population.
The overarching objective is to establish a national AI talent strategy that ensures Americans of all ages and backgrounds have the chance to acquire AI skills that advance economic opportunity. A practical objective is helping people attain AI fluency—an essential capability for using AI in daily work, much as they use laptops, smartphones, software, and the internet today. The historical trajectory of Microsoft and other leading tech firms reinforces a clear lesson: empowering knowledge workers to leverage new technologies is a profound driver of economic growth. The PC/Mobile era created a global economy with more than a billion knowledge workers, and the coming era of AI could create another wave of AI-enabled employment that reaches across services, manufacturing, transportation, agriculture, and government.
As the AI era deepens, some individuals will seek deeper specialization or advanced qualifications. For many people, this learning will take place on the job or through online platforms, and for others, it will involve dedicated study that extends into new AI engineering roles or in-depth business applications that enable the effective design, deployment, and management of AI systems in organizations. The private sector’s experience shows that a dynamic AI ecosystem thrives when education and industry work hand in hand to produce graduates who can contribute immediately to the workforce.
Microsoft’s ongoing efforts illustrate the breadth of the opportunity. In 2025, the company is pursuing a target to train 2.5 million Americans in AI skills that enable them to secure new jobs, pursue new careers, and start new ventures. These efforts are designed to broaden access to AI knowledge and to ensure that a larger share of the workforce can participate in the AI-enabled economy. The focus on community colleges and other accessible education pathways is deliberate, aiming to reach people no matter where they live. The approach recognizes that AI skills are not only technical but also practical, requiring an understanding of how to apply AI in real-world business processes and organizational structures. The intent is to create a scalable, inclusive pathway that can accommodate the rapidly evolving AI landscape and the diverse needs of workers across the country.
In practice, this skilling agenda requires a broad coalition of stakeholders. It demands collaboration with community colleges, faculty, workforce agencies, and industry partners to design curricula that align with regional labor market needs and the demands of AI-augmented industries. It also requires the development of new teaching resources and teacher training programs so educators can guide students through AI-focused content with confidence and competence. The objective is not only to produce a pipeline of skilled workers but also to empower individuals to continue learning throughout their careers as AI technologies advance. This lifelong learning mindset is essential for maintaining competitiveness in a rapidly changing economy.
A core aim of this outreach is to ensure AI opportunities extend beyond metropolitan hubs to rural communities as well. From the National 4-H AI Skills Partnership using Minecraft Education to introduce AI concepts to 1.4 million young people, to the FarmBeats for Students program with the Future Farmers of America, which uses AI to enhance precision agriculture, these initiatives demonstrate how AI education can be embedded in a wide range of contexts. These programs illustrate how AI can be integrated into everyday life and work, expanding the reach of digital literacy and technological fluency. By bringing AI concepts into the classroom and into community settings, these efforts help democratize access to AI, ensuring that future prosperity is not the sole purview of a select few but a nationwide opportunity.
One overarching lesson stands out from these endeavors: AI offers not only new technical tools but also new ways to facilitate learning across disciplines. The aspiration is to equip all Americans with the ability to use AI to pursue higher-paying jobs and more successful careers. This national north star emphasizes equal opportunity, practical skill development, and broad participation in the benefits of AI-driven growth. The ambition is to create an ecosystem where AI literacy becomes a standard, enabling people to adapt to evolving job requirements and seize opportunities that would have been out of reach in a slower-moving economy. The scale and speed of AI innovation make this objective both timely and essential, and it requires a sustained, collaborative national effort to realize its potential.
Beyond training and education, the AI skilling program must address the realities of a rapidly changing labor market. AI will inevitably disrupt certain roles and industries; however, the emphasis remains on maximizing opportunities—helping workers transition to new roles, supporting the creation of new enterprises, and enabling the entire economy to enhance productivity. The experience of Microsoft and other technology leaders shows that thoughtful implementation of AI, combined with explicit workforce development strategies, can minimize disruptions while maximizing the positive impacts of AI adoption. A holistic approach to AI skilling combines curriculum design, career services, apprenticeship opportunities, and industry partnerships to ensure that the benefits of AI reach a broad cross-section of society. This is not only a national imperative but also a strategic opportunity to unleash a new wave of innovation and growth that can sustain long-term prosperity.
AI exports form the third pillar of the American AI opportunity. The objective is to promote an international environment conducive to exporting American AI capabilities while protecting critical AI technologies from potentially adverse acquisition by strategic competitors. The moral and strategic logic is straightforward: a robust export strategy expands the market for American AI products and services, reinforces alliances, and accelerates global deployment of AI innovations in ways that reflect American values and standards for security, privacy, and responsible use. In this regard, the policy approach has to balance open markets with prudent safeguards, ensuring that AI advantages can be shared with trusted partners while preserving core national security interests and competitive advantages.
Generative AI, in particular, has intensified the importance of export strategy. It changes how quickly innovative AI tools can reach global markets and how quickly competitors can scale their own platforms. The international landscape is shaped by competition with China, whose AI sector has grown rapidly and which has pursued strategic emphasis on widespread adoption across developing nations. The result is a dynamic contest in which both speed and scale of deployment matter. The United States must craft a smart, proactive international strategy to accelerate American AI adoption around the world, leveraging private-sector leadership to expand reach and influence.
A historical lesson from telecommunications helps illuminate the path forward. In the past, American and European players built pioneering equipment that defined international standards; however, as Huawei and other Chinese firms invested aggressively and benefited from government subsidies, their products gained prominence globally. This shift changed the competitive dynamic and prompted a reassessment of national security considerations. The experience underscores the need for a strategic approach that combines policy safeguards with aggressive competitive investments to ensure American AI remains the preferred option for countries seeking advanced, trustworthy, and secure AI infrastructure.
Today, the United States enjoys several advantages that, if deployed effectively, can outpace any competitor. American technology—from hardware to AI models to software platforms—often surpasses its rivals in performance and reliability. US-based firms, including Microsoft, have invested heavily in building AI that prioritizes cybersecurity, privacy, digital safety, and responsible use. These commitments help differentiate American AI in a crowded global market and support adoption in diverse regulatory environments. In parallel, the U.S. can build a broad base of international regulatory cooperation among democratic nations in North America, Europe, Asia, and the broader Pacific region. By leveraging existing diplomatic frameworks and expanding AI-focused collaboration, the United States can offer a compelling value proposition that resonates with partners seeking reliable, secure, and innovative AI solutions.
Private capital markets play a critical role in funding and scaling AI infrastructure and deployment. The United States already benefits from a robust private-finance ecosystem that is underscored by deep pools of risk capital and a willingness to finance long-term, capital-intensive AI initiatives. The private sector’s capacity to mobilize funds and build large-scale AI ecosystems—across chips, models, data centers, and cloud-based services—provides a powerful counterbalance to state-led initiatives in other markets. This private-sector advantage is amplified by the United States’ ability to attract foreign investment and to collaborate with international partners who share a commitment to open markets, strong governance, and high standards for security and privacy.
Microsoft’s leadership in this space illustrates how American AI can scale globally through strategic partnerships and large-scale investment commitments. The company has publicly signaled a long-term plan to invest more than 35 billion dollars in 14 countries over three years to build trusted, secure AI and cloud data center infrastructure. This global initiative signals a broader strategy to extend the reach of American AI while maintaining high security standards and trust. The program has already expanded to 40 countries, including deployments in the Global South, where Chinese investments have tended to dominate in other technology sectors. The collaboration with the United Arab Emirates’ sovereign AI company, G42, to extend AI infrastructure to Kenya exemplifies how joint ventures can broaden access to AI capabilities while supporting regional development. Additional collaborations with investment partners like BlackRock and MGX aim to establish a substantial international investment fund—potentially up to $100 billion—to finance AI infrastructure and the AI supply chain, further accelerating global AI deployment and economic integration.
Other major technology players—Google, Amazon, and others—are also significantly increasing their AI investments, signaling a broad, industry-wide push to scale AI capabilities globally. The private sector’s appetite for AI investment is a key driver of the international expansion of American AI. This trend is complemented by the expectation that China will deploy substantial public subsidies to expand its AI technologies internationally, particularly in Africa, Asia, and Latin America. Yet even with China’s aggressive subsidization, the United States maintains a robust comparative advantage in private-sector funding, technical excellence, and the ability to deliver secure, trustworthy AI products and platforms at scale. The optimal public policy response emphasizes enabling continued private-sector advance rather than attempting to match every subsidy with government spending. A pragmatic export-control approach, coupled with strategic, targeted investment in AI capabilities and supply chains for trusted markets, helps maintain American leadership while supporting partners and allies who rely on secure, reliable AI.
The best path forward, then, is to empower the private sector to accelerate innovation and global deployment while implementing export controls that protect critical AI components and security-sensitive data centers without chilling productive growth. This balanced approach supports rapid scale-up, sustained supply chains, and reliable access to AI technology for trusted partners, ensuring that allies and friends have access to American AI platforms and the associated economic benefits. It also underpins the resilience of the global AI ecosystem by reducing dependence on a single supply chain or a single national policy, instead promoting a diversified network of trusted partners who share common security and ethical standards.
In this framework, the United States should maintain a credible, active export-control policy that protects essential AI components while enabling rapid expansion of American AI through trusted channels. The policy must harmonize security considerations with the imperative to sustain a dynamic and competitive private sector that can, in turn, scale AI solutions globally. Too much regulation can dampen the pace of innovation; too little can risk security and strategic misalignment. The objective is to create a calibrated, flexible framework that can adapt to evolving technology, geopolitical shifts, and market dynamics, ensuring that American AI remains at the forefront of global adoption while maintaining a secure, responsible posture.
A pragmatic posture toward international AI leadership emphasizes collaboration with allies, an openness to shared standards, and a commitment to responsible AI deployment. The United States can build on existing diplomatic gains—such as the Abraham Accords and broader technology partnerships—to deepen collaboration with key nations and investors. This approach entails shared investment in AI infrastructure, joint research initiatives, and scalable deployment models that respect privacy, security, and human-centric AI principles. The result would be an international AI landscape in which American platforms and know-how are widely available in ways that promote cybersecurity, trust, and economic opportunity, while advancing democratic norms and resilience against destabilizing actors.
Microsoft’s experience illustrates how to combine a robust private sector with strategic international partnerships. More than a year ago, the company announced an ambitious plan to invest billions of dollars in a network of AI-enabled data centers across multiple countries. This plan aims to create a reliable, secure global AI infrastructure that can support both local economies and multinational enterprises. The effort includes partnerships to extend AI capabilities to regions where access to advanced technology has historically been limited, bringing the benefits of AI to a broader audience. The scale of such investments indicates the vital role that multinational technology firms play in advancing AI adoption worldwide, while also reinforcing the United States’ leadership role in shaping a global AI ecosystem built on shared standards, security, and trust.
The broader objective of AI exports is not merely to sell products abroad but to encourage the adoption of American AI platforms that reflect the United States’ values for security, privacy, and responsible innovation. A successful export strategy requires cooperation among the private sector, governments, and international partners to create environments that maximize positive economic outcomes while protecting critical national interests. The United States can achieve this by combining robust private-sector leadership with selective, well-designed public policy measures that promote international trust and collaboration. By doing so, it can accelerate the global diffusion of American AI technologies in a manner consistent with democratic norms and the protection of fundamental rights and privacy.
The conclusion of this section emphasizes a practical truth: the most important American public policy priority is ensuring that the private sector continues to advance with strong incentives and minimal regulatory drag. Export controls should be designed to protect privacy, security, and national interests without hindering the global competitiveness and supply capacity of American AI developers. By enabling rapid expansion and reliable supply to allied nations, the United States can solidify its role as the central hub of responsible AI innovation and global adoption, while maintaining a leadership position in the ethical, secure, and beneficial use of AI.
The path to broad, sustainable American AI leadership
A practical, ongoing partnership among government, the private sector, universities, and nonprofits is foundational to achieving this vision. The United States must unify diverse stakeholders around a shared goal: a robust, resilient AI ecosystem that drives economic growth, expands opportunity, and elevates the country’s global standing. This collaboration should be anchored in clear policies that stimulate basic research, encourage technology commercialization, and promote widespread AI training and literacy. At the same time, it should incorporate safeguards to ensure that AI is deployed responsibly, with appropriate governance, transparency, and accountability—principles that are essential to maintaining public trust and long-term prosperity.
The private sector’s role remains central in this ecosystem. Firms must continue to invest in AI research and development, scale AI-enabled services, and build infrastructure capable of supporting global deployment. This requires ongoing capital investments in AI hardware, cloud infrastructure, and data centers, as well as sustained commitments to open platforms and collaboration with researchers, startups, and other companies. The private sector can also lead by example in setting high standards for AI safety, security, and ethics, and by sharing best practices with the broader community to accelerate responsible innovation across sectors.
Academic institutions and research networks will continue to be the crucible for AI breakthroughs. Universities play a critical role in basic research, interdisciplinary collaboration, and the training of new generations of AI professionals. Public funding streams for foundational AI research should be preserved and expanded where appropriate, keeping the U.S. at the forefront of discovery. Universities can also serve as testbeds for real-world AI deployments in areas like health care, energy, education, and environmental sustainability, enabling researchers to translate theoretical advances into tangible societal benefits. Strengthened collaboration with industry partners, including joint research centers and industry-sponsored PhD programs, can accelerate the pace at which discoveries are translated into practical, scalable applications.
Nonprofit organizations, professional associations, and community-based groups contribute essential support by addressing workforce needs, improving digital literacy, and offering guidance on responsible AI use. They can help ensure that AI benefits are accessible to a broad cross-section of society, including historically underserved communities. Building these partnerships requires thoughtful policy design that reduces barriers to participation, promotes inclusive training opportunities, and supports local initiatives that align with national AI goals. The synergy among public institutions, private firms, universities, and civil society will be the key to sustaining momentum and broadening the social and economic value of AI.
To realize a national AI strategy, priority actions should include: expanding funding for basic AI research in universities and federal laboratories; accelerating the translation of research into commercially viable AI products and services; building a comprehensive, nationwide AI skilling infrastructure; and promoting international collaboration and standard-setting that expands access to American AI while maintaining security and ethical safeguards. Actionable steps also include supporting community colleges and vocational programs as central nodes in the AI skills network; fostering public-private partnerships to align curricula with current industry needs; and enabling pathways for reskilling workers who are displaced by automation to transition into AI-enabled roles with dignity and opportunity.
A key consideration is to maintain a balance between openness and protection. By embracing an export strategy that expands AI adoption among trusted partners and allies, while implementing prudent safeguards on sensitive technologies, the United States can reinforce its leadership position without compromising national security. The balance must be dynamic, adjusting to evolving technologies, market conditions, and geopolitical realities. The public policy environment should be designed to support rapid innovation and deployment in AI while preserving high standards for security, privacy, and responsible use.
In this context, the United States can build on existing diplomatic and economic relationships to deepen cooperation on AI. This includes leveraging frameworks from global dialogues and alliances to align standards, share best practices, and coordinate on research and investment strategies that advance AI in ways that reflect democratic values. By coordinating with partners in North America, Europe, and Asia-Pacific, the United States can amplify the benefits of AI while mitigating risks. The objective is to create a global AI governance and deployment ecosystem that respects human rights, protects sensitive data, and fosters economic development, innovation, and resilience.
The private sector’s ongoing investments, combined with policy clarity and public support, will be essential to the success of this strategy. A well-calibrated combination of market-driven growth and strategic public policy can accelerate AI adoption across sectors, boost productivity, and generate new opportunities for workers and entrepreneurs. Microsoft’s initiatives illustrate a practical path forward, highlighting the power of large-scale private-sector commitments to build the AI infrastructure that underpins the modern economy. Other tech leaders are pursuing parallel strategies, signaling a broad, industry-wide consensus that AI must be deployed responsibly, securely, and in ways that benefit society as a whole.
A central takeaway is that America’s AI leadership rests on teamwork. The most successful path to a golden AI opportunity lies in a collective effort that draws on the strengths of private enterprise, academic inquiry, and public stewardship. By aligning incentives, coordinating investments, and sustaining a clear national vision, the United States can position itself to win the race for global AI adoption while ensuring that AI serves broad-based prosperity. This is not an isolated enterprise but a shared mission that requires ongoing dialogue, transparent decision-making, and a willingness to adapt as AI technologies evolve. The country’s future prosperity depends on a coherent, collaborative approach to AI that transcends political cycles and regional interests, focusing instead on the long-term benefits of AI-enabled growth for all Americans.
Causes for American Optimism
Looking ahead, there are compelling reasons to be optimistic about American AI leadership in the next four years. The United States benefits from a strong AI technology foundation built on an exceptionally productive and innovative private sector. With disciplined public policy that supports robust basic research, the nation can sustain leadership in AI by ensuring that universities, researchers, and industry work in concert to push the boundaries of what is possible. The education system’s capacity to train AI-literate workers remains a significant strength, enabling the dissemination of AI skills across broad segments of the labor market. The combination of advanced AI platforms, non-profit and industry collaboration, and a government that recognizes the strategic importance of AI can help the economy accelerate growth and create new job opportunities across sectors.
The American educational system, with its universities, colleges, and vocational institutions, has a proven track record of spawning knowledge workers who contribute to the services economy and beyond. The PC/Mobile era catalyzed a global workforce of more than a billion people who were equipped with digital tools and capabilities. As AI enters the stage, there is confidence that a similar wave of AI-enabled workers—across manufacturing, transportation, agriculture, governance, and services—can be developed. This transition will involve building new training pipelines, upgrading curricula, and expanding opportunities for individuals to gain practical AI experience that translates into improved job prospects and higher incomes.
A strong public-private ecosystem is essential for sustaining AI leadership. The private sector’s capacity to innovate, scale, and invest in AI infrastructure is unmatched, and this capability can be amplified by policy measures that encourage investment, protect sensitive technologies, and promote responsible AI deployment. By fostering an environment that rewards innovation while providing a social safety net for workers during transitions, the United States can maintain momentum in AI development and adoption. This approach includes ensuring that the regulatory environment supports experimentation and deployment, while maintaining strong protections for privacy, data security, and human oversight of AI systems.
Education is a key enabler of opportunity in the AI era. By equipping people with the knowledge and skills to operate AI tools effectively, the United States can empower a wide range of workers to participate in high-growth AI-enabled occupations. A robust AI skilling strategy can help reduce inequality by providing pathways for individuals with diverse educational backgrounds to access well-paying jobs in AI-driven industries. The national AI talent strategy must be widely accessible, translating into tangible employment outcomes, entrepreneurship, and career advancement for people across the country. This includes designing programs that are adaptable to regional labor market needs, as well as targeted initiatives for underserved communities, rural areas, and groups that historically faced barriers to entry in advanced technologies. The ultimate aim is to ensure broad access to AI opportunities, enabling a more inclusive, dynamic, and resilient economy.
American capabilities in AI safety, cybersecurity, and responsible deployment are strong differentiators in international markets. U.S. firms are actively pursuing AI that prioritizes privacy, digital safety, and ethical usage, with a governance framework that seeks to build public trust and consumer confidence. This emphasis on responsible AI can foster greater adoption in countries that prioritize governance and standards, expanding the user base for American AI products while reinforcing core democratic values. The combination of trusted AI technologies with a scalable global infrastructure supports broad adoption and provides a competitive edge, inviting international partners to collaborate under shared standards and safeguards.
International cooperation and diplomatic leadership will be essential to achieving these objectives. The United States can leverage its relationships with allied nations to promote AI standards, investment cooperation, and joint research initiatives that advance AI in ways that align with shared security and ethical norms. By working with partners across North America, Europe, and the Asia-Pacific region, the United States can create a more predictable, stable environment for AI deployment, enabling faster scale and broader adoption of American AI platforms in diverse regulatory contexts. These collaborations can help accelerate the global diffusion of AI while maintaining a robust framework for security and human-centric governance.
Finally, private capital markets, alongside government programs and academic research, will continue to fuel AI innovation and expansion. The strength of American capital markets, the depth of private-sector R&D funding, and the capacity to mobilize global investments form a triad that can sustain rapid AI growth. The creation of dedicated investment funds to support AI infrastructure and supply chains, as seen in initiatives like the planned $100 billion fund, can further accelerate AI deployment and contribute to long-term economic gains. Such financial structures complement public investments and public-private partnerships, enabling sustained momentum and resilience in the global AI economy.
The essential takeaway is that the United States has the resources, talent, and institutional capacity to lead in AI by combining a strong technology base, a broad educational and skilling agenda, and a strategic, internationally oriented export and collaboration policy. If the government, industry, and academia work in concert, AI can unlock a new era of productivity, inclusive growth, and national strength.
A forward-looking, practical set of recommendations emerges from this analysis. Invest persistently in basic AI research at universities and federal labs to sustain a steady stream of fundamental discoveries. Expand the national AI talent pipeline through community colleges, vocational programs, and partnerships with industry, ensuring that AI literacy reaches diverse communities and underserved regions. Foster a robust, secure AI infrastructure—especially in data centers and cloud platforms—that can scale globally while protecting privacy and security. Promote international cooperation and standards development that align with democratic values and human-centered governance. And cultivate a balanced export strategy that expands global adoption of American AI by trusted partners while maintaining prudent safeguards to protect national security and competitive advantage.
Conclusion
The United States stands at a watershed moment, with a unique chance to shape the next era of AI-enabled prosperity. By building a solid technology foundation, advancing world-class AI infrastructure, expanding AI skilling for millions of Americans, and pursuing an intelligent export strategy that emphasizes trusted partnerships, the country can solidify its leadership in AI for decades to come. The path forward is collaborative, requiring the alignment of government policy with private-sector innovation, academic discovery, and nonprofit stewardship. The resulting AI ecosystem should be anchored in responsible practices, inclusive opportunity, and international cooperation that reflects American values while delivering tangible benefits to workers, communities, and the broader economy. Together, these efforts can realize a golden opportunity for American AI—an opportunity that extends beyond profitability and national prestige to the daily lives of people who will work, learn, and thrive in an AI-enabled future.
