Elsie Peng, Joseph Briggs, and Sarah Dong, from the team of chief economist Jan Hatzius, explain in a Sept. 13 research note the “measured impact” on GDP from AI is an “intermediate impact” from the Bureau of Economic Analysis (BEA), so it only counts toward final demand when a final product is sold. For example, a semiconductor only shows up in GDP when, say, a laptop is purchased. This means billions of dollars in AI-enabled economic activity isn’t being measured, Peng, Briggs, and Dong argue.

Since the launch of ChatGPT in 2022, they calculate, the dramatic surge in revenues attributed to AI infrastructure has boosted “true GDP” by a staggering $160 billion. This figure highlights AI’s transformative role as a growth engine—but underscores a confounding gap in official government statistics. According to Goldman Sachs, most of AI’s real economic contributions have remained largely invisible in U.S. GDP numbers to date.

The research draws on company reports and government data, revealing spending on AI infrastructure by U.S. firms has soared, a $400 billion increase since 2022. A notable chunk of this spending has been focused on information processing equipment, which spiked at a 39% annualized rate in the first half of 2025.

Digging into ‘true GDP’

To parse out the real domestic economic impact, the Goldman Sachs team adjusted company revenue data by subtracting the effects of inflated prices, foreign sales of equipment produced abroad, and input imports. This resulted in the $160 billion figure, about 0.7% of U.S. GDP since 2022, which translates to roughly 0.3 percentage points of annualized growth.

The same analysts calculate the amount officially counted in measured GDP is far lower—just $45 billion, or 0.2%, since 2022. That reflects only about 0.1 percentage points of annualized growth.

The team also analyzed the four main channels through which AI affects the US economy. First is investment in equipment, such as semiconductors and servers; second is structures such as data centers and power facilities. Third comes intellectual property, including spending on software and R&D, and finally net exports of AI-related goods and services.

However, the analysts warn much of the investment surge was driven by imports, meaning it didn’t contribute directly to net GDP growth, and it grew especially rapidly this year, suggesting it was front-loaded ahead of tariff hikes.

A picture coming into view

Goldman Sachs’ analysis comes as policymakers grapple with how to accurately track the economic impact of a rapidly evolving technology. The analysts caution that while AI is indeed driving meaningful growth, much of it remains hidden from standard indicators.

In the middle of this summer, The Wall Street Journal’s Christopher Mims noted a striking surge in AI infrastructure spending, arguing it was adding more to GDP growth than consumer spending, the backbone of the American economy, responsible for some two-thirds of GDP as measured by the BEA. Retail sales are ticking up, most recently at 0.6% in August, but the American consumer is widely understood to be beleaguered. A picture is emerging of a significant amount of GDP coming from the booming AI sector, and a fatigued economy everywhere else, with slow job growth. If there is an AI bubble, and if that pops soon, a lot could go down with it.

For investors and business leaders, the takeaway is that the U.S.’s AI wave could be more powerful, and potentially more sustainable, than the headline numbers suggest. As the government adapts its statistical methodologies, a fuller picture of AI’s economic footprint could eventually emerge—but for now, it remains largely in the shadows of official calculation.

For this story, Fortune used generative AI to help with an initial draft. An editor verified the accuracy of the information before publishing. 

Every era of seismic technological change has been accompanied by the fear that these will upend livelihoods and disrupt established ways of life.

From the Luddites smashing looms in 19th-century England to autoworkers walking out over the introduction of robots to the factory floor in the 1980s, resistance has flared before either being crushed or subsiding, giving way to the new economies and social orders the technologies ushered in.

Artificial intelligence—a productivity-maximizing tool to some and an untamable threat to others—has asked similar questions of the social contract in the 21st century, and the optimists appear to be winning the day.

President Donald Trump‘s administration considers AI to be eventually and inevitably the driving force of the global economy, and hopes to lead the charge in its incorporation. But as both its capabilities and adoption expand, AI appears poised to outperform humans in certain tasks and in doing so automate away a significant portion of the workforce.

To this challenge, and the economic crises it would inaugurate, some believe the only viable solution may be a policy long-considered fringe: Universal basic income, or UBI.

“Just as the extraordinary crisis of the Great Depression required the bold policy of Social Security, the disruption caused by AI requires an equally bold response—a Social Security for everyone in the form of UBI,” said Gisèle Huff, founder and president of the Gerald Huff Fund for Humanity.

The Risk of AI to American Jobs

Projections regarding AI’s employment impacts are sobering. Huff’s organization recently forecast that it will disrupt 45 million American jobs by 2028—either eliminating these outright or forcing dramatic shifts in how they are done. Management consulting giant McKinsey, meanwhile, predicts 30 percent of U.S. roles will be automated by the end of the decade.

As for who will be impacted, experts offer a number of answers. Huff predicts that white and blue collar alike could be on the chopping block, with impacts spread across gig and stable professions and routine jobs like data entry and customer service among those facing the greatest risk.

Benjamin Lockwood, a professor of business economics and public policy at the University of Pennsylvania’s Wharton School, believes jobs involving “repetitive or formulaic tasks” will be the most easily displaced.

“Entry-level white‑collar roles are heading for a reckoning as routine work gets automated,” economic analyst Le Dong Hai Nguyen told Newsweek. “The apprenticeship model for young college graduates is cracking as firms favor lean, expert‑led teams enabled by AI.”

To economist Evelyn Forget, the better question may be “which jobs can AI not replace?”

Some roles have already been replaced, chatbots having largely done away with live customer service agents online, and a number of CEOs have cited their increased focus on AI adoption as fueling recent layoffs in the tech space.

While estimates regarding the scale and type of roles that will be affected vary, the consensus is that AI’s impact will be nontrivial and demand adaption.

UBI to the Rescue?

“I believe the rise of AI makes UBI more necessary, given that it will likely lead (at some point) to a large portion of the workforce being automated, and would mainly be a means of covering the basics,” said Aran Nayebi, an assistant professor of machine learning at Carnegie Mellon University.

“AI adoption is likely to create unemployment, especially among jobs that include routine cognitive tasks. This highlights the potential need for UBI adoption,” Rita Fontinha, a professor of Strategic Human Resource Management at Henley Business School, told Newsweek.

As well as job displacement, AI risks deepening wealth inequality—concentrating the gains among those who own or are able to leverage its abilities, while throwing the remainder into the same basket of the formerly employable unemployed.

“The few who ‘own’ the technology will do well, and the very lucky few who are still employed to ‘manage’ the stables of AI-enhanced workers,” Forget told Newsweek. “The rest of us will scramble for those very few jobs.”

However, beyond the challenges posed by AI making a basic income perhaps more necessary, Fontinha believes the economic possibilities it presents could make a no-strings-attached, government-provided income more possible.

“As the productivity benefits of AI become clearer, the argument that society can afford a baseline income for all becomes more credible,” she said.

This argument has been made by some of UBI’s most notable advocates. Andrew Yang‘s 2020 presidential platform centered on the idea that AI would cause irreparable disruptions to the workforce, a problem that could be solved in part by a monthly, $1,000 “Freedom Dividend” funded by new taxes on the tech-driven economy and greater government efficiencies.

Could UBI Become a Reality?

Houston Frost is chief product officer at payment technology firm Usio, and has worked on a number of UBI programs across the U.S. These include the New York City Bridge Project, which provided unconditional cash support to low-income mothers, and the Chicago Resilient Communities Pilot, which gave 5,000 households a monthly stipend of $500 for 12 months.

Frost told Newsweek that the potential for a basic income program to transition from novel idea to mainstream policy may hinge on societal perception, which he notes have “not been particularly supportive of the concept of UBI.”

“That said, a weak economy can definitely spur the U.S. into action,” he added. “We saw what the government was willing to do (and the people willing to accept) during the 2008 credit crisis, and again in 2020 with the pandemic, when hundreds of billions of dollars were distributed to businesses and individuals.”

UBI will also likely draw opposition from fiscal conservatives, who believe that such programs demand unsustainable spending and tax increases, while also pointing to the potential inflationary effects of unconditional “freebies.”

“The problem with UBI is the ‘U,'” according to Carl Frey, an economic historian at Oxford University. “Making payments universal sends scarce funds to people who don’t need them.” An alternative, he told Newsweek, would be some form of “negative income tax,” whereby those below a certain financial threshold receive payments.

These ideas are currently being explored, including through direct cash assistance pilots in the U.S. and abroad. While these seldom erase the need for a labor-derived income stream, they are establishing the parameters for new and radical ways of supporting a citizenry beyond traditional social safety nets.

As the effect of AI on jobs becomes clearer—whether this be an explosion in unemployment or more subtle evolutions in the workforce—the idea of a guaranteed income may no longer be read as radical. Instead, it may emerge as a necessary and inevitable policy as society once again attempts to keep pace with the machines.

Read Newsweek‘s Full Interview With Houston Frost Below

Which jobs are most at risk from the growing adoption of AI?

“We’re already seeing AI replace humans in several areas. The most visible are those in customer service and support, with AI agents now handling millions of customer interactions once handled by live agents over chat, email and even phone.

“Another large wave of replacements is likely to come in transportation with autonomous vehicles now operating in several major cities. These two alone account for several million jobs.

“Other roles at risk in the near-term include administrative and clerical positions as well as certain positions in finance, banking and accounting, particularly those that are data-driven and repetitive.

“In total, well over 10 million jobs in the U.S. are likely at risk over the next 10 years, and at the current pace of development that figure could be conservative.

Who will benefit from the growing productivity offered by AI?

“AI has the potential to benefit everyone, depending on the use case, but at the same time presents challenges to certain sectors. Customer service and tech support will provide faster resolutions and more accurate answers. In general, increased productivity should reduce the cost of services and increase their availability.

“Realistically, the income generation and wealth creation effects of AI will assuredly not be as evenly distributed. AI will disproportionally benefit capital holders (companies and investors) over workers. The tech industry’s well-known oligopolistic [dominated by a few large firms] tendencies will likely lead to extreme concentration of wealth. High-skilled workers will see income growth, while low-skill workers will be competing for a decreasing number of job openings.

“The question then becomes, how will society, government and businesses respond to this shifting dynamic. It’s hard to believe we will see businesses volunteering their increasing profits to the public.

“However, the deflationary pressure created by the increasing use of AI would ultimately create pain for businesses and their investors. The reduction of labor costs via automation, efficiency gains, and increasing digital goods and services would all serve to push prices down. If you layer job losses and lower income growth on top of that, it’s not a great recipe for economic success.

Does the rise of AI make UBI more necessary or increase the possibility of its adoption?

“Currently, the U.S. government primarily employs the powers of the Federal Reserve to keep both inflation and unemployment within acceptable ranges. If the Fed were to jump into action in the face of deflation and high unemployment, they would essentially increase the availability of credit. The problem is, it’s not easy to get a loan when you don’t have a job, regardless of how low interest rates are.

“As such, if AI continues to be as successful as these early stages indicate, the government will almost certainly need new methods to balance the economy, and Universal Basic Income will undoubtedly be explored.

“Many nonprofits and local governments are already experimenting with numerous direct cash assistance and pilot UBI programs. The company I work for, Usio, has helped distribute over $250 million in just the past two years through various cash-assistance and pilot UBI initiatives across almost every major city in the U.S.

“However, current UBI pilots do not fully replace the income of a full-time job, offering between $250-$1,500 per month, and are limited in duration, making payments over six to 24 months. Typically, these pilots focus on specific demographics or life stages, such as youths aged 18-24, pregnant or expecting single mothers, students and teachers, refugees, and food and farmworkers. The primary goal of these UBI pilots is to help individuals and families through a transition period. They aren’t meant to provide lifelong or even long-term income streams.

“It’s also important to note that in general, society has not been particularly supportive of the concept of UBI. It’s taken decades for advocates of UBI to finally see the first pilot programs come to fruition. It’s only been in the last three years that university researchers are able to study the effects of these programs in the U.S.

“That said, a weak economy can definitely spur the U.S. into action. We saw what the government was willing to do (and the people willing to accept) during the 2008 credit crisis, and again in 2020 with the pandemic, when hundreds of billions of dollars were distributed to businesses and individuals.

“While AI may not directly lead to a widespread embrace of UBI solutions, its effects on the economy certainly could. People and politicians in our country make decisions on a perilously short time scale. And, economic pain is one of our greatest motivators. So perhaps we will see a broadening acceptance of higher taxes for business and wealthy individuals, with the proceeds going to help balance the economic scale through programs like UBI. But, it’s unlikely to happen until the majority of us feel the pain.

The artificial intelligence (AI) revolution is now the main engine driving the growth of some of the world’s most valuable companies. Many of these technology giants use AI not only to cut costs or boost efficiency, but to help transform entire industries and build platforms that are likely to be the drivers of global expansion over the next decade.

For investors with a long-term mindset, the smartest move now is to target the best of these businesses based on their proven cutting-edge technologies, scale, and long-term vision. Let’s highlight two of these AI players taking a leading role and find out why they are well-positioned to create significant value in the long run.

1. Nvidia

Semiconductor giant Nvidia (NVDA -1.55%) is the undisputable leader in the global AI infrastructure market. The company’s cutting-edge GPUs have become the backbone of AI workloads worldwide and help power massive cloud data centers and enterprise AI applications.

Nvidia’s recent financial performance highlights its business momentum. In the second quarter of fiscal 2026 (ended July 27, 2025), revenue surged 56% year over year to $46.7 billion, driven by explosive demand for its new Blackwell platform. The company began production shipments of its new Blackwell Ultra GB300 racks in the second quarter, marking a smooth transition from the earlier GB200 systems. Net income was also up 59% year over year to $26.2 billion.

Nvidia has transformed itself from a gaming-focused GPU provider to a full-stack AI platform player. Beyond hardware, the company has built a strong competitive moat with its proprietary Compute Unified Device Architecture (CUDA) parallel computing software platform, used to optimally program GPUs. With over 5.9 million developers using CUDA worldwide, the company has created an exceptionally strong developer ecosystem that raises switching costs for clients.

Nvidia has also made rapid advances in AI-optimized networking solutions. Management highlighted that NVLink 72, an advanced interconnect architecture used in Blackwell AI platform, enables each rack (enclosure used to organize multiple data center servers) to operate as a single computer, significantly improving efficiency for reasoning and agentic AI workloads — an advantage that is becoming critical as data centers face power constraints.

Nvidia is also focusing on opportunities in areas such as robotics, automotive, and automation. Spending on AI infrastructure globally is projected to be somewhere between $3 trillion and $4 trillion by the end of the decade. Nvidia is well-positioned to be a key recipient of this spending.

Although the company trades at a rich valuation of 39.5 times forward earnings, Nvidia’s robust growth prospects make it an exceptional pick for long-term investors — even at elevated valuation levels.

2. Microsoft

Microsoft (MSFT -1.13%) is positioning itself as a foundational platform in the AI-powered economy, building a comprehensive ecosystem of AI products and large-scale technology infrastructure. Once known primarily for its productivity suite and Windows operating system, the company is now embedding Copilot virtual AI assistant and agentic AI capabilities across its core offerings. Subsequently, the company is reshaping how clients organize and execute workflows.

Copilot (across all applications) counts over 100 million monthly active users, and its backend is powered by GPT-5. The company expects Copilot to help users connect with specialized AI agents for solving business challenges.

Microsoft is also strengthening the cloud, data, and model infrastructure that powers Copilot and the growing ecosystem of AI products. The company’s Azure computing business, which forms the hardware layer of its technology infrastructure, crossed an annualized run rate of $75 billion, up 34% year over year at the end of the second quarter. Although the company has built over 400 Azure data centers across 70 regions and has added over 2 gigawatts of new capacity in the past year, it is still seeing demand outpacing supply. This highlights the growth potential in the data center space.

Microsoft Fabric, an AI-powered data and analytics platform, is rapidly gaining traction, with revenue soaring 55% year over year in the second quarter. The company is also positioning Azure AI Foundry as the model layer to help clients build and manage AI applications and agents at scale. Foundry was used by over 80% of the Fortune 500, while the Foundry Agent services are powering agent development at more than 14,000 enterprises.

Microsoft’s security offerings are also strengthening its business. The security business caters to nearly 1.5 million customers and had already generated over $20 billion in revenue in fiscal 2023 (ended June 30, 2023). The security business will become even more significant, as the rising adoption of generative AI has also added new ways in which hackers can break into an enterprise system. Additionally, it is also tightly integrated into Copilot and the Microsoft 365 suite, which further strengthens its value proposition.

Microsoft trades at about 37.4 times forward earnings. This rich valuation, however, is supported by its accelerating AI-driven growth. With rising Copilot adoption, expanding Azure scale, and a fast-growing security business, it is proving to be a smart buy for long-term investors.