The Impact Of Artificial Intelligence Ai On Economic Growth A

Bonisiwe Shabane

-Dec 28, 2025, 2:13 PM

the impact of artificial intelligence ai on economic growth a

Daniel Björkegren is an assistant professor of international and public affairs at Columbia University, New York City, New York, USA. How will artificial intelligence reshape the global economy? Some economists predict only a small boost — around a 0.9% increase in gross domestic product over the next ten years1. Others foresee a revolution that might add between US$17 trillion and $26 trillion to annual global economic output and automate up to half of today’s jobs by 20452. But even before the full impacts materialize, beliefs about our AI future affect the economy today — steering young people’s career choices, guiding government policy and driving vast investment flows into semiconductors and other... Why evaluating the impact of AI needs to start now

Given the high stakes, many researchers and policymakers are increasingly attempting to precisely quantify the causal impact of AI through natural experiments and randomized controlled trials. In such studies, one group gains access to an AI tool while another continues under normal conditions; other factors are held fixed. Researchers can then analyse outcomes such as productivity, satisfaction and learning. Yet, when applied to AI, this type of evidence faces two challenges. First, by the time they are published, causal estimates of AI’s effects can be outdated. For instance, one study found that call-centre workers handled queries 15% faster when using 2020 AI tools3.

Another showed that software developers with access to coding assistants in 2022–23 completed 26% more tasks than did those without such tools4. But AI capabilities are advancing at an astounding pace. For example, since ChatGPT’s release in 2022, AI tools can now correctly handle three times as many simulated customer-support chats on their own as they could before5. The better, cheaper AI of tomorrow will produce different economic effects. Brooke Tanner, Josie Stewart, Nicol Turner Lee You have full access to this open access article

The application of artificial intelligence (AI) across firms and industries warrants a line of research focused on determining its overall effect on economic variables. As a general-purpose technology (GPT), for example, AI helps in the production, marketing, and customer acquisition of firms, increasing their productivity and consumer reach. Aside from these, other effects of AI include enhanced quality of services, improved work accuracy and efficiency, and increased customer satisfaction. Hence, this study aims to gauge the impact of AI on the economy, specifically on long-run economic growth. This study conjectures a positive relationship between AI and economic growth. To test this hypothesis, this study makes use of a panel dataset of countries from 1970 to 2019, and the number of AI patents as a measure of AI.

A text search query is performed to distinguish AI patents from other types of innovations in a public database. Employing fixed effects and generalized method of moments (GMM) estimation, this paper finds a positive relationship between AI and economic growth, which is higher than the effect of the total population of patents on... Furthermore, other results indicate that AI’s influence on growth is more robust among advanced economies, and more evident towards the latter periods of the dataset. Avoid common mistakes on your manuscript. The developments in computer science and digital technology, including artificial intelligence (AI) and machine learning, naturally led to their application in key sectors such as healthcare, finance, manufacturing, and transport.Footnote 1 Their increasing use... In neoclassical and endogenous economic growth models, for example, technical change brings about increases in productivity, leading to economic growth.

Hence, breakthroughs in computing technology should also entail increases in growth rates. In particular, the last 60 years have witnessed a shift in production from traditional inputs to more information and communications technology (ICT)-based, capital-intensive tools. The introduction of modern computers and the Internet in the early 1990s, and more recently, AI, led to changes in the methods of production. In keeping with the rise of new technologies, Zeira (1998) proposed an economic growth model adopting technological innovations that reduce labor inputs but require more capital.Footnote 2 Furthermore, more recent empirical studies on the... 2011; Nchake and Shuaibu 2022). Thus, it is only expected that advancements in ICT may have a positive effect on overall productivity and economic growth.

The collective decisions we make today will determine how AI affects productivity growth, income inequality, and industrial concentration Economists have a poor track record of predicting the future. And Silicon Valley repeatedly cycles through hope and disappointment over the next big technology. So a healthy skepticism toward any pronouncements about how artificial intelligence (AI) will change the economy is justified. Nonetheless, there are good reasons to take seriously the growing potential of AI—systems that exhibit intelligent behavior, such as learning, reasoning, and problem-solving—to transform the economy, especially given the astonishing technical advances of the... AI may affect society in a number of areas besides the economy—including national security, politics, and culture.

But in this article, we focus on the implications of AI on three broad areas of macroeconomic interest: productivity growth, the labor market, and industrial concentration. AI does not have a predetermined future. It can develop in very different directions. The particular future that emerges will be a consequence of many things, including technological and policy decisions made today. For each area, we present a fork in the road: two paths that lead to very different futures for AI and the economy. In each case, the bad future is the path of least resistance.

Getting to the better future will require good policy—including The first road concerns the future of economic growth—which is largely the future of productivity growth. The US economy has been stuck with disturbingly low productivity growth for most of the past 50 years, except for a brief resurgence in the late 1990s and early 2000s (Brynjolfsson, Rock, and Chad... Most advanced economies now have the same problem of low productivity growth. More than any other factor, productivity—output per unit of input—determines the wealth of nations and the living standards of their people. With higher productivity, such problems as budget deficits, poverty reduction, health care, and the environment become far more manageable.

Boosting productivity growth may be the globe’s most fundamental economic challenge. On one path of the productivity fork, AI’s impact is limited. Despite the rapidly improving technical capabilities of AI, its adoption by businesses may continue to be slow and confined to large firms (Zolas and others 2021). The economics of AI may turn out to be of a very narrow labor-saving variety (what Daron Acemoglu and Simon Johnson call a “so-so technology,” such as an automated grocery checkout stand), instead of... Displaced workers might disproportionately end up in even less productive and less dynamic jobs, further muting any aggregate benefit to the long-term productivity growth rate of the economy. In a new paper, MIT Institute Professor Daron Acemoglu predicts that artificial intelligence will have a “nontrivial, but modest” effect on GDP in the next decade.

Artificial intelligence research is filled with dramatic forecasts. AI will affect almost 40% of jobs around the world, according to the International Monetary Fund. It will increase global GDP by $7 trillion — or 7% — over 10 years, predicts Goldman Sachs. Or it will grow between $17.1 and $25.6 trillion annually, if you prefer to go with McKinsey’s estimate. And these projections are relatively conservative compared with others. In a new paper, “The Simple Macroeconomics of AI,” MIT Institute Professor Daron Acemoglu has a more conservative estimate of how AI will affect the U.S.

economy over the next 10 years. Estimating that only about 5% of tasks will be able to be profitably performed by AI within that time frame, the GDP boost would likely be closer to 1% over that period, Acemoglu suggests. This is a “nontrivial, but modest effect, and certainly much less than both the revolutionary changes some are predicting and the less hyperbolic but still substantial improvements forecast by Goldman Sachs and the McKinsey... Acemoglu, a 2024 Nobel laureate in economic sciences, also looked at other economy-wide wage and inequality impacts expected from generative AI. For the paper, Acemoglu looked at prior scholarship that analyzed which tasks will be exposed to AI and computer vision technologies and concluded that nearly 20% of all tasks in the U.S. labor market could be replaced or augmented by AI.

But only about a quarter of those tasks — or 5% economy-wide — could be profitably performed. (In the other 75% of cases, costs for implementation may exceed the benefits.) The recent emergence of generative artificial intelligence (AI) raises the question whether we are on the brink of a rapid acceleration in task automation that will drive labor cost savings and raise productivity. Despite significant uncertainty around the potential of generative AI, its ability to generate content that is indistinguishable from human-created output and to break down communication barriers between humans and machines reflects a major advancement... If generative AI delivers on its promised capabilities, the labor market could face significant disruption. Using data on occupational tasks in both the US and Europe, we find that roughly two-thirds of current jobs are exposed to some degree of AI automation, and that generative AI could substitute up...

Extrapolating our estimates globally suggests that generative AI could expose the equivalent of 300mn full-time jobs to automation. The good news is that worker displacement from automation has historically been offset by creation of new jobs, and the emergence of new occupations following technological innovations accounts for the vast majority of long-run... The combination of significant labor cost savings, new job creation, and higher productivity for non-displaced workers raises the possibility of a productivity boom that raises economic growth substantially, although the timing of such a... We estimate that generative AI could raise annual US labor productivity growth by just under 1½pp over a 10-year period following widespread adoption, although the boost to labor productivity growth could be much smaller... The boost to global labor productivity could also be economically significant, and we estimate that AI could eventually increase annual global GDP by 7%. Although the impact of AI will ultimately depend on its capability and adoption timeline, this estimate highlights the enormous economic potential of generative AI if it delivers on its promise.

We study how generative artificial intelligence (AI) affects short-run growth across countries. Our analysis covers 56 economies and 16 industries. We combine two elements. First, industries differ in how much they rely on cognitive and knowledge-based tasks, and so differ in their exposure to AI. Second, countries differ in their readiness to adopt new technology, based on their digital infrastructure, human capital, innovation capacity and regulatory frameworks. We measure industry exposure using data from the United States and country readiness using the International Monetary Fund's AI preparedness index.

We then link these measures to the change in real value added in each country-industry pair between 2022 and 2023. Existing research focuses mainly on the United States and large advanced economies. Much less is known about how emerging market and developing economies stand to benefit from AI in the near term. Yet the structure of their economies differs, and many have weaker digital infrastructures. This raises the possibility that AI may widen global income gaps. Our paper provides one of the first global assessments of how sectoral exposure and country readiness interact to shape short-run growth.

We find that industries that rely more on knowledge and skilled labour gain the most from AI. Countries with stronger digital infrastructure, clearer regulatory frameworks and a more skilled workforce also see larger growth effects. Advanced economies tend to score higher on these dimensions, so they are likely to benefit more from generative AI in the short term. Many emerging market economies gain less, partly because their production structures are more concentrated in low-exposure sectors and partly because they are less prepared to adopt new technologies. These patterns hold even when we account for the use of robots. Overall, the spread of AI could widen global income gaps in the near future.

The Impact Of Artificial Intelligence Ai On Economic Growth A

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