How AI Is Affecting the Global Economy

Artificial intelligence (AI) is designed to replicate and augment human intelligence by training machines to think and learn like humans. The concept has been around for decades, basically since the advent of the computer, and it has generally helped human beings live better, more productive lives. Advances in computing power over the past several years have led to the development of tools and applications that have made AI more accessible to the global population. These artificial intelligence tools can be used for recreation or pleasure, but the business and commercial applications are revolutionary in allowing machines to perform the production tasks of both manufacturing and service employees at a fraction of the cost.

The latest advances have come in the field of agentic AI, which is AI software capable of figuring out how to complete a task with minimal instruction. Compared to generative AI, which is reactive and requires human prompts, agentic AI “learns” from past inputs and proactively navigates third-party sites to make decisions or take actions. This is all done with minimal, or perhaps no, human prompting. An example would be in content creation, where agentic AI can generate marketing materials, articles, and social media posts. Generative AI, while still very useful, currently needs a human to initiate and oversee the generation of all these materials. Read on to learn why the need for AI has grown over the years, plus the benefits and risks our advisors are already starting to see in the industry.

The need to increase productivity in developed economies

Enhanced productivity can be an elixir for economic growth. While there are many demand-side variables to consider when assessing the health of a macroeconomy, its ultimate growth from the supply side is simply a function of the growth of the labor force population multiplied by its productivity. As economies have developed and grown wealthier over the centuries, population growth tends to slow as children become more expensive—not so much from a hard cost perspective, but in opportunity cost reflected in the time taken to raise them. Allowing liberal immigration can help compensate for weak population growth, but for cultural and political reasons, many developed societies are hesitant to allow a free flow of immigrants. If the productivity of the existing labor force does not increase in these “closed” societies, long-term economic growth will suffer.

Increased productivity allows economies to grow in a noninflationary mode as employees “earn” their raises through higher production. The promise that AI could offer incrementally higher revenues without a concurrent increase in hiring and other operating expenses is obviously enticing to management. With the use of artificial intelligence tools, companies do not need to pass the labor cost increase on to consumers to protect their margins. If inflation remains contained in this productivity-led growth environment, monetary policy will be able to stay relatively loose with no need to raise interest rates. Capitalist economies, driven by profit-seeking businesses, constantly seek higher productivity from their input factors, whether labor or capital. The ability to make capital investments that increase the output of the labor force has led to innovation and wealth creation, improving the quality of life in developed economies.

Victims and beneficiaries of artificial intelligence

The global economy appears to be on the precipice of another disruptive surge of innovation. AI will automate routine manual tasks in both the manufacturing and services sectors. While some jobs will be lost, new roles will be created that require greater problem-solving skills and creativity. There will likely be another widening of the income gap as the newly created roles receive enhanced compensation to match the productivity increase. The resultant political hand-wringing will revive the somewhat tired debate around success in a capitalist economy, where winners see a big windfall and others receive less of a share, but in a much more prosperous society. We’ve forecast some of the anticipated workforce impacts on the chart below.

AI’s impact on the workforce

Throughout human history, as innovations disrupt the existing order, there is always an outcry about lost jobs and displaced employees. In almost all historical eras of significant technological advance, innovation ultimately creates as many jobs as it kills. Perhaps instead of destroying jobs en masse, AI could help existing workers increase their skill sets and be more productive. Yes, certain jobs will be rendered obsolete, but new jobs that we cannot imagine today will be created in an economy that will be much better off for embracing innovative products or services.

While there is a general perception that developed economies have an inherent advantage over developing countries in leveraging AI to improve productivity, the bigger advantage may lie in the systemic differences between countries. When the renowned economist Milton Friedman visited a construction site in communist China in the 1960s, he questioned why the many workers on a canal project were using shovels to dig out the canal with no modern earthmoving equipment in sight. In response, the project manager gushed about how many jobs the project had created. Friedman quipped that if the ultimate goal was to create jobs rather than build the canal, the workers’ shovels should be taken away and replaced with spoons. While this is an admittedly extreme and blunt example, differences in the willingness of companies and countries to utilize the advancements in AI will likely be the most important determinant of widening income gaps in the coming years.

AI’s impact on global industries

Another concern regarding the pervasive influence of AI is that it will eventually be able to do everything a human can do, and likely better. The persistent fear that we could lose control over AI, with disastrous consequences, has fueled demand for governmental scrutiny.

Certain sectors of the economy will be major beneficiaries of the AI revolution. Not only will they generate revenue through the sale of innovative products, but they will also marshal AI advances to improve productivity and profit margins. The technology and communication services sectors are obvious winners, as their products gain market share. The semiconductor companies that produce the expensive AI chips are at the forefront of the movement, led by Nvidia, which was recently the first public equity to surpass $4 trillion in market capitalization. The health care sector is using AI to revolutionize diagnostics. Less obvious sectors that should grow as AI becomes more pervasive are power generation, data warehouses, and insurance underwriting. The generational growth in power demand sparked by AI should lead to a large increase in jobs in the power generating industries.

Jobs will indeed be lost in other sectors. For example, will we need human weather forecasters in the near future? To bring it closer to home, there is evidence that AI programs are being used to make financial analysis fast and easy. AI could conceivably work with the analytical and advisory community in preparing diligence memos on new investment opportunities, market research, competitive benchmarking, pitch decks, and portfolio deep dives. Seasoned veterans in the financial services industry probably need not worry as the interpretation of data will likely continue as an important skill set, but there may be significantly less demand for the inexperienced but brilliant intern fresh out of a major university. AI can also play a role in further democratizing the investment experience because armchair investors will have the same access to data and data analytics as professional investors.

The current implications of AI for companies and the global economy

The growth of AI applications is leading to extreme competition for talent in the space. It appears that most companies will soon need to fill Director of Artificial Intelligence or Chief AI Officer roles. Meta (formerly Facebook) just recruited a very senior professional from Apple to fill such a role. A dozen Google DeepMind employees recently moved to Microsoft AI. Beyond the pressing human resource needs, running AI data centers entails a massive demand for electricity. A recent quote, “electricity is the new oil,” caught our attention by referencing the commodity that fueled (pun fully intended) the industrial revolution of the late 19th and early 20th centuries. The demand to run AI applications is likely to drive electricity prices up for everyone. The once defensive, highly regulated utilities industry has been one of the top sector performers in the S&P 500 over the last 12 months of an equity bull market. While it has been a great environment for investors in the sector, there will likely be some political backlash targeting AI for spurring higher energy costs.

AI is increasing GDP growth rates

Spending on AI and the productivity gains already realized have begun to positively impact the GDP growth rates of both the U.S. and global economies. For most of this decade to date, capital spending in the U.S. has been growing, but at a seemingly slow rate as investment in energy projects lagged in a relatively low commodity price environment. But a deeper look shows that capital spending on technology and intellectual property has been strong all decade, with the bulk of that spending going toward productivity-enhancing investments in both the manufacturing and services sectors. Spending on data centers, graphics processing units, server infrastructure, and power have helped drive rather strong GDP growth in the U.S. Estimates of the contribution of spending on AI to GDP growth are as high as 1.5% for U.S. growth and 1.0% for global growth.

China, Taiwan, and South Korea have also seen a meaningful increase in chip sales that is driving their respective GDPs higher. With roughly 90% of AI applications produced in English, there seems to be a push toward “sovereign AI,” where countries can maintain their distinct culture, history, and unique intelligence. China has boldly stated that it wants to be the global leader in AI by 2030. Based on its recent track record with technological advances, it will be interesting to see whether it innovates, borrows, or cobbles together some combination of the two to get there.

Increase in capital expenditures for AI infrastructure

During the second quarter of the 2025 U.S. earnings season, planned investment in AI and its current utilization was largely addressed head on by executive teams to manage the message before analysts had an opportunity to question the effort. It appears the incredibly ambitious capital expenditure plans of the hyperscalers (Amazon, Google, Microsoft, and Meta) in standing up data centers remain intact. These companies alone spent a cumulative $95 billion on capital expenditures in the second quarter and are forecast to spend $325 billion in their respective fiscal years. Continued investment by large technology firms in AI infrastructure will keep demand strong for semiconductors, software, and services.

The AI-related sectors of the market should be large contributors to overall earnings growth both this year and next. Analysts will pressure companies in other sectors to show an active and tangible utilization of AI to improve product offerings and gain greater efficiency in producing the product or service. The returns on AI investments across sectors and industries should start to show up in 2026 earnings reports and lead to notable increases in the growth rate of earnings per share over the rest of the 2020s.

How technology like AI has impacted the economy historically

There have been legitimate comparisons of this era of AI to the 1990s era of the internet, as they both involved the use of technological innovation to improve overall economic productivity and increase the long-term potential growth rates of maturing economies. Attaching or associating AI to a company description is likely to lead to a boost in the stock price in the same way that attaching “.com” did in the ’90s. Perhaps a lesson learned from the dot-com era is to refrain from bidding stock prices so high for companies that have yet to become profitable. The high valuations currently seen in the AI space are arguably primarily for companies that have proven—albeit sometimes short—sales and earnings growth histories. It is always difficult to discern a valuation bubble until after it has already burst, but the current valuation of AI-related equities using traditional metrics such as price-to-earnings and price-to-cash-flow ratios appears reasonable given the rapid growth rates, high customer retention rates, and demonstrated pricing power.

Trying to pick the winners in these eras of technological innovation can be difficult. Investors will soon be looking for indications of a return on the massive capital spent by the hyperscalers, who have historically been asset-light in the conduct of their businesses. Not every capital investment will produce similar returns, but they all must invest if they want to participate in the exciting AI-driven productivity trend. The owners of the technology that ultimately drives innovation usually create the most enterprise value. Infrastructure investments are typically required to maximize the distribution and impact of any new technology. Investment in data centers and energy appear necessary to maximize the benefit of the AI revolution.

Investors clamoring to buy into the AI theme in the public and private markets will need to understand both their direct and indirect exposures during times of equity market pullbacks and corrections. Another lesson from the ’90s is that many portfolio managers became surprisingly overinvested in the internet theme in sectors outside of technology. Advertisers in the consumer discretionary sector and global investment banks in financial services were examples of two industries that derived much of their increased sales and earnings growth from the internet theme. When the theme ended in a burst of the valuation bubble, these more defensive sectors did not provide the intended protection. Advances in portfolio analytics and factor analysis may help instill greater portfolio management discipline in this current environment.

Competition in the AI space

It is far from clear at this time who the ultimate market share winners will be as AI applications are introduced and used by consumers and businesses. A new browser war seems to be developing with upstart competitors like Perplexity and OpenAI seeking to make their technologies and products more useful to corporations. The goal is to take market share from Google, whose Chrome product became the ultimate winner in the last browser war that began in the ’90s. To defend itself, Google is making large, preemptive capital investments to maintain its lead.

Creative destruction and the ability to infiltrate the apparent dominance of the current market share leaders has been a hallmark of U.S. capitalism in the post-World War II years. We are in the early innings of the latest surge in innovation. It is never a smooth ride, but it should ultimately lead to a pronounced improvement in the overall global standard of living as well as the minting of a new generation of billionaire investors and entrepreneurs.

If you would like to learn more about investing in market sectors that are involved with artificial intelligence, contact your Cerity Partners advisor or request an introduction.