How AI could supercharge America

School children learning coding in computer science class. (ReeldealHD on Offset via Shutterstock)

The American economy is like a flabby giant. Its size and strength are still impressive, but it huffs and puffs when faced with certain challenges. The federal government runs trillion-dollar deficits – even in good years. Birth rates are falling. Schools are failing many kids. Infrastructure is rusting out faster than we can replace it. And none of these are new problems. They are the consequences of years of cultural drift, neglected maintenance, complacent citizens, and weak leadership. 

Yet under this blubbery exterior, the U.S. economy still boasts some strength. Today that is coming from technology companies, big and small, which are fueling the country’s economic growth. In September 2024, Mario Draghi – the former president of the European Central Bank – noted in a major report  on competitiveness that while the European Union and the United States had boasted comparably sized economies in 2000, since then, per-capita real disposable income in the United States had almost doubled the EU level. The main reason for this shift and the widening productivity gap between the two economies, Draghi concluded, was the tech sector.  

Artificial intelligence could bring this sector’s strength to the rest of the American economy. Properly applied, AI could become a general-purpose technology on par with or even surpassing electricity or the internet. It could boost productivity, expand opportunity, and revitalize our bloated and sluggish systems. AI-driven productivity increases could help balance our national budget, fill the gaps left by an aging workforce, remake education, and drive scientific and health care discoveries and innovations that underpin prosperity. AI offers a path to a robust, muscular, fit American economy.  

The opportunity is America’s to seize. The United States leads the world in AI research and investment, although other countries, especially China, are in hot pursuit. If we miss this moment, it won’t be because technology failed us – it will be because our politics did. Fear, fragmentation, and bureaucratic overreach could choke off the very growth the United States desperately needs. The country currently faces three significant political challenges in this domain: whether to allow a patchwork of state laws to strangle AI innovation before it scales; whether to let our children learn with AI; and whether to build the physical power and computing resources needed to let AI proliferate. 

How the United States meets these challenges will determine whether we use AI to whip the country’s economy back into shape – or decide instead to resign ourselves to a couch-potato economy, with all the stagnation that would bring. 

Move slow and break nothing 

Important parts of the U.S. economy today have become undisciplined, shortsighted, and slow. Last year, despite low unemployment and steady GDP growth, the federal deficit hit $1.8 trillion. The share of eighth graders scoring “proficient” in math was just 28%, down six percentage points since 2019. The country’s fertility rate remains well below the replacement level. And projects to build basic necessities such as transmission lines or high-speed railways routinely take a decade or more to permit and construct. 

America’s capacity to do big things has atrophied. Our last real productivity boom ended two decades ago. Outside of technology, the economy is barely growing. As of mid-2025, just four tech firms accounted for roughly 60% of year-over-year stock-market gains. The so-called Magnificent Seven largest U.S. tech companies make up almost 50% of the total value (by market capitalization) of the NASDAQ 100 stock index.  The U.S. economy leans heavily on our tech companies. 

But AI could reinvigorate the rest of the economy, and the country along with it. Consider the following. In November 2022, OpenAI released ChatGPT as an experiment. Despite the company never intending to build a mass consumer product, ChatGPT became the fastest-adopted technology in history, hitting 100 million users in two months. The app ignited a surge of investment that spread far beyond chatbots. By 2024, private AI investment in the United States had reached $109 billion, and the number is still growing rapidly. 

ChatGPT is not the first time a technological breakthrough has driven excitement about AI. But this time is different. Machine learning, which is the core process underpinning modern AI, uses algorithms trained on vast data sets to recognize patterns and make predictions. This approach is proving highly generalizable. It can already draft contracts, model proteins, translate languages, and guide robots. Machine learning is making its way into every field that runs on data. And in the 21st century, that’s nearly all of them. 

AI, in other words, will define our era, and the good news is that the United States leads the world in this technology. U.S. companies designed and trained the AI models, constructed the data centers that run them, and developed the applications that bring the power of AI to users. America dominates the AI industry today, in investment, revenue, and innovation.  

AI won’t solve America’s problems on its own. But it could make almost every problem easier to solve – if we don’t get in our own way. 

U.S. Secretary of Education Linda McMahon visits Alpha School Austin on Sept. 09, 2025, Austin, Texas. (Photo by Rick Kern/Getty Images for Alpha School)

Barrier one: The 50-state trap 

Unfortunately, too many American leaders currently treat AI as a reason to panic. In 2024, state lawmakers introduced 635 AI-related bills, enacting 99. By mid-2025, that number had ballooned to more than 1,100 proposals. The National Conference of State Legislatures reports that 38 states adopted or enacted approximately 100 measures in just the first six months of this year. 

The intentions of these laws vary: to make AI safe, protect consumers, prevent bias, regulate deepfakes, or restrain tech giants. But whatever the goal, the outcome of this flurry of lawmaking is the same: a minefield for the companies required to comply with regulation. Unlike these laws, modern AI isn’t built state by state. It’s trained on global data, deployed on cloud servers located around the world, and used in ways that cross borders in real time. In other words, modern AI is not a single product situated in a single place; it’s a distributed set of constantly evolving services. Trying to govern AI locally is like trying to use your thermostat to control the weather. 

The threat posed to tech leadership created by this patchwork of regulation isn’t theoretical. Each new state mandate adds conflicting definitions, overlapping audits, and redundant reporting requirements that companies must struggle to fulfill. Pro-regulation states with large markets – like California and New York – essentially set the rules for everyone else. Big companies must waste huge amounts of money and time complying with all the rules – but they probably can absorb the costs. Startups can’t. The results will be predictable: fewer startups, slower product launches, chilled investment, and innovation driven offshore.  

One need only look at Europe – where well-intentioned but cumbersome AI and technology rules have slowed research and driven talent to the United States – to see what impact such a regulatory approach could have here. If the United States commits its own version of this mistake by allowing individual states to race for the most restrictive standards, the whole country will lose. 

The U.S. Congress should act before that happens. It should preempt most state AI laws and set a single national framework for model training and deployment – an approach that treats AI as the interstate infrastructure it is. A coherent federal policy would consistently protect users, clarify responsibilities, and streamline compliance for innovators. The right model would mirror what has worked for past transformative technologies: uniform, light-touch rules, allowing for open competition and space for experimentation. Anything else will weigh down our economy with onerous amounts of legal paperwork. 

Barrier two: Banning the future of education 

The second threat to America’s AI dominance – and the technology’s potential to transform our economy – is more emotionally fraught but no less destructive: overreacting to the use of AI by children. 

The fear is understandable. The growth of the internet has taught us to be wary of tech’s unintended effects. Parents today have many reasons to be protective. But banning AI outright in our classrooms or making it harder for children to use – moves some lawmakers have already proposed – would be an act of educational malpractice. 

That’s because AI tutors could become the most powerful learning tool since the printed book. At Alpha School in Austin, Texas, for example, AI systems coach students through their core academic work in just a few hours – and then the students spend the rest of the day building drones, running businesses, or exploring the outdoors. Alpha School is also developing a platform called Timeback that aims to empower educational entrepreneurs to create personalized, one-on-one instruction for less than $1,000 a year per student. 

This isn’t science fiction; it’s a working prototype of what individualized education could look like. Properly used, AI tutors could democratize elite instruction, helping kids learn at their own pace, in their own style, with real-time feedback and fewer bureaucratic barriers. 

But lawmakers are letting fear drive policy. Bills intended to protect kids could undercut the very feedback loops that power AI-driven educational tools. Overly strict rules protecting privacy, for example, would prevent AI systems from effectively tracking students’ progress or spotting their subtle learning patterns. And a tutor that can’t observe is a tutor that can’t teach. These and other poorly considered laws could drive AI innovators away from education to less legally fraught areas, even though the country desperately needs more innovation in this field.  

We haven’t banned microscopes because they reveal too much detail, or calculators because they could potentially replace our arithmetic skills. Instead, we have equipped our educators to use such tools responsibly and trusted them to train our students to do the same. For similar reasons, the solution to how to deploy AI in education today is not prohibition but thoughtful application and experimentation. Parents should have options and schools should have significant flexibility. Privacy laws should deter the misuse of information rather than the mere gathering of it. An open, pluralistic approach would nourish what works and weed out what doesn’t.  

Our current education system is failing too many of our children. Denying students access to the tools that will define their generation would not be appropriately cautious – it would be shortsighted and reckless. 

An Amazon Web Services data center in Ashburn, Virginia on Oct. 28, 2025. (Lexi Critchett/Bloomberg via Getty Images)

Barrier three: The building bottleneck 

AI is software, but its progress ultimately depends on our ability to build significant physical infrastructure. And America no longer builds as it once did. The mid-20th century United States erected an entire modern world in a generation. It poured concrete for highways, raised power plants, wired cities, and built the grid that powers everything from suburbs to supercomputers. The country had a bias for action. 

Today, that bias is gone. The very laws designed to manage progress have become tools to prevent it. When Congress passed the National Environmental Policy Act (NEPA) in 1969, it was intended to strengthen environmental stewardship. But the law now functions as a procedural labyrinth and the most powerful tool in the NIMBY toolbox. Environmental reviews for infrastructure projects take a median of more than two years, an average of nearly four, and often generate thousands of pages of analysis with little measurable benefit. The result is paralysis by paperwork. Every major project – solar farms, wind installations, data centers, transmission lines – can be delayed for years by bureaucracy and litigation. 

Yet AI needs physical infrastructure. Data centers – which really should just be called supercomputers – are the modern equivalent of factories. All the online services we use, including AI services, run on these supercomputers housed in large warehouses. Training a cutting-edge model and serving its users require significant amounts of computing power and energy. (Contrary to popular belief, data centers don’t really require that much water; they use significantly less of it than many industrial factories or agriculture products.) 

The growth of AI has increased the demand for data centers and the infrastructure they require. In particular, AI requires more energy production and distribution. But the United States struggles to build new power sources and connect them to the grid quickly enough. Most of the United States has expanded capacity very slowly since the 1970s. Only Texas, which operates a deregulated “connect-and-manage” grid, has grown quickly, adding more than twice as much as any other grid operator in the country between 2021 and 2023. The state’s dynamic energy market is a major draw for new data centers, with hundreds of billions of dollars in planned investments testifying to the grid’s stability and recovery since Winter Storm Uri in 2021. 

If the United States can’t speed up its permitting and building processes, the AI boom will stall. The world’s most sophisticated algorithms are useless without electrons to power the computers. 

Congress should therefore treat infrastructure improvement as a national security priority. It should replace our current process-for-process’-sake approach to new construction with outcome-based environmental standards. It should set firm timelines for reviews and limit their scope. It should expand categorical exclusions for low-impact projects. And it should limit injunctions to cases of clear and imminent harm. 

At the same time, federal and state agencies should coordinate to unclog interconnection queues and modernize the grid. The future of AI – and much else – depends on abundant, reliable energy. Building it is the precondition for greatly increasing our prosperity. 

Fear or abundance 

America has been here before. We’ve stood on the edge of a technological breakthrough, uncertain whether to seize it or smother it. We faced it with the railroads, the electrification of cities, the interstate highway system, and the dawn of the internet. In each case, abundance won out over fear, though not always quickly and not always cleanly. The choice before us now is the same: to treat AI as a threat to be contained or as an opportunity for renewal. 

Choosing abundance means trusting the American people to build, learn, and adapt. It means allocating government rules between the federal government and states in a way that promotes experimentation rather than chills it. It means giving every child access to the tools of the age rather than locking them behind digital fences. And it means rediscovering the courage to build – not someday, but now. 

The alternative is a future in which AI progress happens elsewhere, U.S. schools stagnate while those in other countries accelerate, and the next generation of American innovators grows up under a regime of control rather than freedom. 

That would be a major societal failure. 

AI is not a silver bullet for all our problems, but it could be the catalyst that restarts broad American dynamism. The question is not whether AI will transform the world. It will. The question is whether the United States will lead this transformation, or if we will comfortably watch others from the sidelines. 

We can still choose abundance. The United States remains the most capable society on earth for translating invention into prosperity. We’re a bit doughy and out of practice, but we still have the talent, the institutions, the capital, and the culture of risk taking that every other country envies.  What we need is to give ourselves permission to shed the unnecessary deadweight, to exercise our entrepreneurial muscles, and to wrestle optimistically with the challenges ahead.