Is the Industrial Revolution a Precedent for Explosive AI Growth?

 

Is the Industrial Revolution a good precedent for explosive economic growth today?

July 27, 2026

One line of evidence that AI might lead to explosive economic growth is the precedent set by the Industrial Revolution. For hundreds of years — 1252 to 1652, to be precise — the compound annual growth rate of per capita real GDP in the UK was around 0.07%. It then began to accelerate, settling into a new compound rate of around 1.02% per year by 1850, which it held until 1913. In other words, growth accelerated by roughly 15 times before; the argument goes that this should make us humble about predicting it can’t happen again, and perhaps we should be open to accelerations of 10 times or more today.

I think this argument is overstated and the analogy between a 10× acceleration today and the acceleration that occurred during the Industrial Revolution is misleading. The goal of the first part of this post is to provide evidence for two claims:

1. At the outset of the Industrial Revolution, annual growth that was 10× the long-run average was relatively common.
2. In the contemporary world, annual growth that is 10× the long-run average for the world is much more rare.

The second part of this post characterizes the acceleration that occurred during the Industrial Revolution in terms of the standard deviation of year-to-year variation in growth rates. Applying the same approach to contemporary growth suggests that an IR-style acceleration would take growth in frontier economies to around 2.8% per year — meaningfully faster than today, but well below the 10× claim that is often advanced.

Why go through this exercise? A common reaction to claims that AI will lead to annual growth rates in excess of 20% per year is skepticism and incredulity — it would be so far outside historical experience. A common retort is that the same incredulity would have been wrong in the 1700s: had someone been told that future growth would be 10× the average and dismissed it, they would have made an error. The goal here is to rescue that initial reaction. A 10x acceleration today is not the same thing as a 10x acceleration in 1700. A person living in the 1700s would have been asked to envision good years becoming much more common — a rate they had already experienced many times. A person today is being asked to envision a qualitatively different kind of economic dynamics, one that falls several standard deviations outside the norm for the world today.

All estimates use the Maddison Project Database 2023, which reports GDP per capita in 2011 USD and population in thousands. The final section considers some objections to the relevancy of this analysis.

How common was 10× faster growth in the pre-IR UK?

We will start by establishing that it was quite common for growth to exceed 10× the long-run average in the UK prior to the Industrial Revolution. Over 1252–1652, the long-run average was 0.30% per year. The compound growth rate over this period — the rate at which wealth actually accumulated across generations — was around 0.07% per year. Roughly 10× this compound rate — around 0.66% per year — was exceeded in about 46% of years. (This figure is not sensitive to the exact window chosen: the compound growth rate ranges from 0.07% to 0.18% across plausible alternative start and end years, and the share of years exceeding 10× that rate ranges from about 40% to 50%.).

Economic statistics from hundreds of years in the past are highly unreliable, so we also consider 20-year compound average growth rates to eliminate year-to-year fluctuations. The mean compound rate across all 20-year windows is 0.06% per year, making the 10x threshold around 0.6%. About 17% of 20-year windows exceeded this threshold, implying that generation-long runs of 10× faster growth were not unheard of prior to the Industrial Revolution.

As a robustness check, we identified eight modern countries (Benin, Burundi, Chad, Haiti, Senegal, Sierra Leone, Togo, and Zimbabwe) with characteristics similar to the pre-IR UK regarding GDP per capita, population, and growth rates. Their average compound growth rate is 0.35%/yr, and annual growth rates exceeding 10× that — around 3.5% per year — were exceeded in about 19% of country-years.

Further analysis of the entire contemporary dataset shows that 10× faster growth is much more common for slow-growing countries. Among economies averaging 0–1%/yr, 94% experienced at least one 10× year between 1986 and 2022. This share falls to 22% for countries averaging 1–2%/yr and to essentially zero for those above 2%/yr.

How common is 10× faster growth today?

In Britain around 1700, a year of 0.66% growth — ten times the compound rate — was not unusual, as about one year in two already exceeded that threshold due to the volatility caused by harvests, wars, and disease. A permanent tenfold acceleration would have felt like a run of good harvests that simply kept coming.

Today, the story is very different. In the contemporary USA, 10× the compound growth rate implies annual growth of roughly 19% per year, a level Americans living today have never experienced. Looking at the whole world from 1950–2022, only 0.76% of country-years experienced growth in excess of 19%.

Of the 89 country-years that exceeded 20% growth, most fall into two categories: oil and resource windfalls (e.g., Kuwait, Libya, Equatorial Guinea) or post-conflict recovery (e.g., Lebanon, Bosnia, Rwanda, Iraq). These cases represent GDP returning to previous levels rather than an economy operating in a new gear. A third, smaller category involves early industrialization (e.g., South Korea in 1953, Botswana in the early 1970s), which might be a partial analogue for AI if it unlocks a fundamentally new production frontier.

In sum, a 10× growth acceleration today would be a qualitatively new way for the economy to operate, whereas, during the Industrial Revolution, it would have felt like an ordinary good year becoming more frequent.

The standard deviation approach

If we understand the Industrial Revolution as “more of the good years, fewer of the bad years,” we can use the standard deviation (SD) of annual growth rates as a ruler. The annual SD for various samples are:

• Pre-IR UK (1252–1652): 6.9%
• Modern analogue countries: 5.5%
• USA (1950–2022): 2.3%
• All countries (1950–2022): 6.2%

The Industrial Revolution represented a 15× acceleration (0.07% to 1.02%), which is an increase of about 0.17 standard deviations when measured against the modern analogue distribution. Applying this same 0.17 SD increase to the US frontier baseline of 1.9% would take growth to about 2.8% per year. In contrast, a genuine 10× increase today (to 18.9%) would require an increase of 3.1 to 7.5 standard deviations, depending on the sample used.

Some potential objections and replies

Objection 1: Pre-industrial and industrial growth have different mechanisms. One might argue that pre-industrial fluctuations (weather, war) are irrelevant to technological progress. However, the speed of economic change may be governed by factors beyond technology, such as property rights transfer, labor preferences, savings rates, and market size. These factors may limit growth speed in both eras.

Objection 2: Sensitivity to the definition of interval. Some argue that measuring growth over one-year intervals is arbitrary. However, shorter intervals are useful because failing to hit a growth rate on a short interval makes it less likely to be hit on a longer one, much like a runner's 400m time informs their potential for a mile race. The Industrial Revolution did not require unusually fast short-run rates by its own standards, but explosive growth today would require hitting short-run rates that are unusually fast by contemporary standards.

A closing observation

The agricultural revolution likely followed a similar pattern, where "good years" simply became more common relative to "bad years". In neither the Industrial nor the agricultural revolution did short-run growth rates likely surprise contemporary observers by dramatically accelerating relative to existing precedents.

Reproducing this analysis The full code and data are in the growth-acceleration repository. Data is sourced from the Maddison Project Database 2023. Dependencies include pandas, numpy, matplotlib, and openpyxl. The analysis is generated by running python3 analysis.py.