AI may start to boost US GDP in 2027
Generative artificial intelligence has the potential to automate many work tasks and eventually boost global economic growth: Goldman Sachs Research forecasts AI will start having a measurable impact on US GDP in 2027 and begin affecting growth in other economies around the world in the years that follow.
The foundation of the forecast is the finding that AI could ultimately automate around 25% of labor tasks in advanced economies and 10-20% of work in emerging economies, Goldman Sachs economists Joseph Briggs and Devesh Kodnani write in the team’s report.
They estimate a growth boost to GDP from AI of 0.4 percentage points in the US, 0.3 percentage points on average in other DMs, and 0.2 percentage points on average in advanced EMs by 2034. In other emerging markets, Goldman Sachs Research forecasts a smaller boost from AI given adoption will probably take longer and AI exposure will likely be lower.
“We expect this automation to drive labor cost savings and free up workers’ time, some of which will likely be allocated to new tasks,” Briggs and Kodnani write. The ultimate size of those effects will depend on how capable AI actually becomes and how it’s implemented.
How much can AI improve productivity?
In the baseline scenario, the Goldman Sachs Research economists estimate AI could increase US productivity growth by 1.5 percentage points annually assuming widespread adoption over a 10-year period. They expect similar effects in other major developed markets, and a somewhat smaller impact of 0.7-1.3 percentage points in most emerging economies given their higher share of employment in sectors with low AI exposure like agriculture and construction.
Taken at face value, those kinds of productivity gains would suggest a substantial jump in GDP growth around the globe. Assuming workers aren’t permanently replaced by automation and there’s capital to support the increase in productivity, the increase in productivity could boost long-run worldwide GDP by as much as 15%. But Briggs and Kodnani think the net effect will be somewhat lower than that for two key reasons.
First, our economists already include technological innovation in their economic forecasts. Simply adding their estimates for the boost in productivity from AI to the current trend would likely result in some double counting. They note that information and communication technology (ICT) investment has already been the main driver of productivity growth in major economies over the last 20-30 years.
And second, the underlying productivity growth has been slowing. Academic research suggests that growth in total factor productivity (calculated by dividing real output by the combination of labor and capital inputs) tends to slow over time as countries develop, except during rare “regime shifts” such as those triggered by the first and second industrial revolutions.
Predictions of AI superintelligence seem premature
Is generative AI different? Some observers have argued that it could be a paradigm-shifting technology that ushers in a new regime for productivity growth. Equity analysts in Goldman Sachs Research have identified sectors where they think this could happen, including in healthcare and drug discovery, cybersecurity, design, and software development. Some have gone a step further and view recent advancements in AI as a meaningful step towards a “superintelligence” that is able to process information, formulate views, and innovate beyond the capability of humans.
For now, the more extreme predictions appear “very premature, especially given 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 mostly drive efficiency gains by automating less difficult but time-consuming tasks, thereby empowering workers to engage in more productive activities.”
In the meantime, much will depend on the adoption timeline. Historically, productivity booms driven by prior milestone technologies — such as the electric motor and personal computer — have lagged the initial innovation by more than a decade. These innovations only began to show up in macroeconomic data once roughly half of affected businesses had adopted the technology.
“We have been relatively cautious on the AI adoption timeline,” Briggs and Kodnani say. “While a rapid acceleration in AI-related investment is ongoing for leading technology and professional services firms which are developing and pioneering the use of AI, the effects on productivity that we have estimated will require the implementation of AI across a broader set of industries and job functions.”
AI’s effects on GDP will take time to emerge
Surveys of businesses and executives indicate that they generally anticipate a small impact from AI on activity and hiring needs in the next 1-3 years but a much larger impact in the next 3-10 years. Likewise, Goldman Sachs Research expects broad-based adoption to accelerate in the US beginning in the second half of this decade. The adoption timeline may be even more drawn out elsewhere, as the US and other advanced economies have historically led in the adoption of milestone technologies.
Taken together, our economists’ model indicates AI will probably have a positive impact on GDP over the next decade — but it will take a few years to show up in the numbers. Goldman Sachs Research is leaving its forecasts unchanged until at least 2027 for the US and 2028 for other economies. How the timeline for adoption plays out, the amount of ICT investment that’s displaced by AI spending, the extent of AI’s emerging capabilities, as well as potential regulatory barriers, will all influence how and to what extent these economic gains are realized.
“Our estimates reflect a balanced consideration of these risks, and provide a template for analyzing the longer-run effects of AI on the macroeconomy,” Briggs and Kodnani write. “In our view, the development of capable AI is likely to be among the most consequential macroeconomic stories of the 21st century, with important implications for relative economic performance, financial market returns, and longer-run interest rates.”
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