U.S. Annualized Real GDP Growth
U.S. Annualized Real GDP Growth
Experts expect U.S. growth of 2.7% a year to 2029 and 3% to 2049.
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Our Analysis
How do we interpret these results
When not told to condition on a progress scenario, experts, superforecasters, and the public broadly agree on near-term GDP growth, with median forecasts of 2.7%, 2.5%, and 2.5% annualized real GDP growth for 2025–2030, respectively—broadly in line with recent historical rates. Scenario assumptions make a substantial difference, however. Under Rapid Progress, the median expert expects 4.0% annualized growth to 2030 and 5.0% to 2050, while under Slow Progress those figures fall to 2.3% and 2.5%. Superforecasters are more conservative under Rapid Progress, forecasting only 3.5% annualized growth to 2030 and 3.4% to 2050—below expert estimates—suggesting superforecasters are more skeptical that AI-driven gains will translate into GDP growth even under optimistic capability scenarios. Differences between experts and the public are small and generally not statistically significant, with both groups expecting somewhat stronger long-run growth under Moderate and Rapid Progress scenarios than superforecasters.
Forecasts by scenario
Median forecasts from experts for each scenario
| scenario | 2029 | 2049 |
|---|---|---|
| Unconditional | 2.7 pp | 3 pp |
| Slow Progress | 2.3 pp | 2.5 pp |
| Moderate Progress | 3 pp | 3.5 pp |
| Rapid Progress | 4 pp | 5 pp |
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* Denotes non-overlapping bootstrapped confidence intervals between group aggregates.
Rationale analysis
The main lines of reasoning driving the spread in estimates
Adoption lag
The most frequently cited reason for why even strong AI capabilities are unlikely to translate quickly into meaningful GDP growth is that institutional, societal, and regulatory frictions will slow diffusion: "Even if AI capabilities move quickly, the economy doesn't just flip a switch. Companies have to reorganize. Capital has to cycle through. Workers have to move into new roles."; "Software progress can move quickly, but GDP responds to capital replacement cycles, regulatory approval, and human trust, all of which move much more slowly."
Demographic and structural headwinds
Lower-growth respondents cite an aging population, a declining labor force participation rate, declining immigration, and a high U.S. debt load as drags on GDP that AI cannot easily offset. "Given slower population growth, an aging workforce, and moderate productivity gains, a reasonable central estimate for annual real GDP growth would be between 1.7% and 1.9%," writes one, and another that "without immigration, the U.S. population would start to shrink in 2033." Higher-growth respondents tend to emphasize the potential of AI to decouple GDP growth from population growth: "In 'Rapid,' Al substitutes for labor (robotics) and accelerates innovation (R&D), removing traditional bottlenecks."
The base rate and Fed/CBO projections
Lower-growth respondents anchor heavily on the stability of U.S. real GDP growth at roughly 2–2.5% annualized over recent decades. One points to the fact that "numerous technological breakouts have occurred over the past 100 years…(electrification, mass customer product manufacturing, global supply chains, radio and television rollouts, digitization, computer technology, an infinite set of advances based on the internet…)" as a reason to be skeptical that the emergence of AI will result in GDP growth "significantly different than [what] the historical record indicates." Another notes that "The Federal Reserve's FOMC published dot plot still projects the long term US GDP growth rate at slightly less than 2%," and another that the CBO is projecting 1.6% growth over the next 30 years. Higher-growth respondents often argue AI's potential to automate cognitive labor and accelerate R&D make it different; that if it "becomes a strong collaborator across sectors, automates large portions of knowledge work, and improves R&D productivity, leading to sustained productivity gains," that this will "eventually put GDP growth above the base rate."
Job cuts and demand destruction
A significant subset of lower-growth respondents worry that rapid AI progress could paradoxically reduce GDP by destroying jobs and consumer purchasing power. One writes, "If managers can replace large fractions of employees with Al, with no obvious alternative employment opportunities, there will be less wealth to be spent among the general populace, which will reduce demand for goods/services and hurt GDP," and another that "if large swaths of the population are out of [a] job, consumption will suffer." Higher-growth respondents tend to assume displaced workers will be reabsorbed or view automation as a solution to labor scarcity: "The integration of autonomous systems in factories and homes overcomes traditional labor shortages and operational bottlenecks."
Non-AI related risks
Many lower-growth respondents emphasize that GDP over these horizons will be shaped more by tariffs, trade wars, kinetic wars, political instability, debt crises, and climate change than by AI progress: "Will there be a significant recession during the two dates or a major military conflict or another pandemic?"; "Tariffs and the U.S.-China rift…will reduce the overall number of buyers for any good or service produced in the United States."; "For 2050 I am also accounting for possible climate change shocks that reduce GDP growth." Higher-growth respondents tend to either not address these factors or to cite one or some of them as a reason to widen their lower confidence interval.
Timing mismatch between AI uplift and measurement windows
A number of respondents argue that even if AI delivers a meaningful GDP boost, it may manifest as a temporary bump that doesn't align neatly with the 2025–2030 or 2045–2050 measurement periods. "My 2045–2050 growth predictions are lower than my predictions for peak five year growth by 2050, because I think it is possible that there will be a temporary period of highly transformational effects and peak growth will have already passed by 2050," writes one forecaster. Another adds that "moderate progress might lead to elevated growth for a decade or so, before returning to the long-term average."
Existential risk
A minority of respondents—mostly those forecasting extreme variance rather than simply high or low growth—flag the possibility that human economic activity ceases entirely. One writes: "I think there's a >10% chance that 'human economic activity ceases' for all 2050 10th percentiles," and another that "I expect the rapid progress scenario to very likely lead to societal collapse hence the negative GDP forecast." Relatedly, a few respondents raise the concern that GDP may become a meaningless metric under rapid progress: "Does GDP mean anything for Moderate and Rapid scenarios by the year 2045? It seems similar to trying to measure the current Human GDP in terms of the Crow economy."
Rationale examples
High-quality rationales from forecasters across the range
Lower-growth respondents
I think most activities in the economy are about navigating equilibria, not raw optimization power. Therefore, and since I expect diffuse AI capabilities, I don't expect massively out of the ordinary gains in the rate of GDP growth, even in the very rapid progress scenarios.
Many of the most frequently cited breakthrough examples require physical engineering rather than purely cognitive advances. 'Cure cancer' is not a software problem alone. It requires wet lab automation, controlled experimentation, regulatory validation, and interaction with extremely expensive and sensitive hardware systems. Connecting autonomous agents directly to multimillion dollar laboratory equipment introduces both technical and existential risk. Granting systems access to reagents capable of producing biological hazards raises obvious safety concerns. These constraints slow deployment even when underlying intelligence is capable.
Social resistance may ultimately prove even more significant than integration complexity. Human reactions such as 'I do not trust it' are emotional rather than epistemic, but they still shape policy and adoption. Individuals and institutions are wired to protect status, expertise, and organization.
Given slower population growth, an aging workforce, and moderate productivity gains, a reasonable central estimate for annual real GDP growth would be between 1.7% and 1.9%. Under a moderate AI acceleration scenario, AI could significantly boost productivity, increase total factor productivity (TFP) growth and raise labor productivity, particularly in services and knowledge-intensive sectors. In a rapid progress scenario, TFP growth could exceed 2% annually, with broad automation of cognitive labor. In such a case, annualized GDP growth could reach up to 5%.
The one scenario I believe is exceedingly unlikely is a major acceleration of economic progress. Either the technology is not as successful as the hype predicts it will be, or it will be as successful as predicted in the optimistic scenarios, which will lead to a complete displacement of most of the society from economic activity. Unlike in previous technology iterations, there is no space for the displaced humans to be reintroduced even after re-training as the strong AI should affect all economic activities. Given the current utter lack of societal level preparation for such a scenario, I am deeply sceptical this will not lead to a full collapse.
Higher-growth respondents
If AI systems can truly 'collapse years-long research timelines into days' and deploy Level-5 robo-taxis that go anywhere, the traditional constraints on economic output—specifically labor shortages and R&D bottlenecks—are effectively removed. In this world, the marginal cost of intelligence and physical logistics approaches zero. I believe this would trigger a productivity boom comparable to the electrification of the 1920s or the IT [information technology] boom of the 1990s, but compressed into a much shorter timeframe, leading to a massive, albeit potentially volatile, spike in real output.
By automating standard research, data analysis, and software tasks, AI frees human experts to focus exclusively on high-impact breakthroughs. The integration of autonomous systems in factories and homes overcomes traditional labor shortages and operational bottlenecks. AI significantly lowers the marginal cost of services, pushing growth far beyond historical 2-4% values.
The U.S. economy has strong momentum and structural advantages for AI adoption, justifying an above-consensus baseline. The big uncertainty is whether AI proves transformative enough to overcome serious long-term demographic and fiscal headwinds, which is why the near-term scenarios cluster tightly while the long-term ones diverge dramatically. The bullish lean reflects a belief that the U.S. tech ecosystem and flexible labor markets position it better than most to capture AI-driven productivity gains.
Currently it makes economic sense to offshore economic activity from wealthy countries to poorer ones to increase profits by benefitting from cheap labour. If AI delivers cheaper labour than developing countries then not only might the US stop offshoring that work, but it would also make sense for investors in developing countries to move their investments to the US too. You could have a scenario where global investment becomes extremely highly concentrated.