AI may start boosting US GDP in 2027

AI may start boosting US GDP in 2027

Generative AI has the potential to automate many work tasks and ultimately boost global economic growth: Goldman Sachs Research predicts that AI will begin to have a meaningful impact on US GDP in 2027 and begin to impact growth in other economies around world in the following years.

Basing the forecast is the finding that AI could eventually automate about 25% of work tasks in advanced economies and 10-20% of work in emerging economies, Joseph Briggs and Devesh Kodnani, economists at Goldman Sachs, wrote in the team’s report.

The researchers estimate that the boost to GDP growth from AI would be 0.4 percentage points in the United States, 0.3 percentage points on average in other emerging markets, and 0.2 percentage points on average in advanced emerging markets by 2034. In other emerging markets, Goldman Sachs Research expects a smaller increase. Adoption of AI will likely take longer and exposure to AI will likely be less.

“We expect this automation to result in labor cost savings and worker time, some of which will likely be allocated to new tasks,” Briggs and Kodnani wrote. The ultimate magnitude of these effects will depend on how capable AI actually is and how it is implemented.

To what extent can artificial intelligence improve productivity?

In a baseline scenario, economists at Goldman Sachs Research estimate that AI could increase productivity growth in the United States by 1.5 percentage points annually assuming widespread adoption over a ten-year period. They expect similar impacts in other major developed markets, and a somewhat smaller impact of 0.7 to 1.3 percentage points in most emerging economies due to their higher share of employment in sectors with low exposure to AI such as agriculture and construction.

Taken at face value, these types of productivity gains indicate a significant jump in GDP growth around the world. Assuming that automation does not permanently replace workers, and that there is capital to support the increase in productivity, the increase in productivity could boost global GDP in the long run by up to 15%. But Briggs and Kodnani believe the net effect will be somewhat less than that for two main reasons.

First, our economists already include technological innovation in their economic forecasts. Simply adding their estimates of increased productivity thanks to AI to the existing trend is likely to lead to some double counting. They point out that investment in ICT has already been the main driver of productivity growth in major economies over the past 20 to 30 years.

Second, underlying productivity growth has been slowing. Academic research suggests that growth in total factor productivity (calculated by dividing real output by the mix of labor and capital inputs) tends to slow over time as countries develop, except during rare “systemic transitions” such as those sparked by the First and Second Industrial Revolutions. Revolutions.

Predictions of artificial superintelligence appear premature

Is generative AI different? Some observers have claimed that it may be a paradigm-shifting technology that heralds a new regime for productivity growth. Equity analysts at Goldman Sachs Research have identified sectors where they believe this could happen, including healthcare, drug discovery, cybersecurity, design, and software development. Some have gone further and view recent developments in artificial intelligence as a meaningful step toward “superintelligence” capable of processing information, formulating viewpoints, and innovating beyond the ability of humans.

For now, the most extreme predictions seem “extremely premature, especially in light of the well-documented limitations of current AI models,” Briggs and Kodnani write. “We therefore maintain our view that for the foreseeable future, generative AI will predominantly drive efficiency gains by automating less difficult but time-consuming tasks, thus enabling workers to engage in more productive activities.”

In the meantime, much will depend on the adoption timeline. Historically, productivity booms driven by earlier prominent technologies—such as the electric motor and the personal computer—lag behind initial innovation by more than a decade. These innovations only began to appear in macroeconomic data after nearly half of the affected companies had adopted the technology.

“We’ve been relatively cautious about the timeline for AI adoption,” Briggs and Kodnani say. “While rapid acceleration in AI-related investment continues for leading technology and professional services companies developing and using AI, the impacts on productivity we estimated will require implementing AI across a broad range of industries and job functions.”

The effects of AI on GDP will take some time to be felt

Surveys of companies and executives indicate that they generally expect little impact of AI on activity and hiring needs in the next 1-3 years but a much greater impact in the next 3-10 years. Likewise, Goldman Sachs Research expects widespread adoption in the United States to accelerate beginning in the second half of this decade. The adoption timeline may be longer elsewhere, as the United States and other advanced economies have historically been leaders in adopting important technologies.

Taken together, our economists’ model suggests that AI will likely have a positive impact on GDP over the next decade — but it will take a few years for it to show up in the numbers. Goldman Sachs Research leaves its forecasts unchanged until at least 2027 for the United States and 2028 for other economies. How the adoption timeline is implemented, the amount of ICT investment displaced by AI spending, the extent of emerging AI capabilities, as well as potential regulatory barriers, will all impact how and to what extent these economic gains are achieved.

“Our estimates reflect a balanced consideration of these risks and provide a model for analyzing the long-term macroeconomic impacts of AI,” Briggs and Kodnani wrote. “In our view, the development of capable AI is likely to be among the most important macroeconomic stories of the 21st century, with important implications for relative economic performance, financial market returns, and long-term interest rates.”


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