Technology
Long Waves: The History of Innovation Cycles
Long Waves: How Innovation Cycles Influence Growth
Creative destruction plays a key role in entrepreneurship and economic development.
Coined by economist Joseph Schumpeter in 1942, the theory of “creative destruction” suggests that business cycles operate under long waves of innovation. Specifically, as markets are disrupted, key clusters of industries have outsized effects on the economy.
Take the railway industry, for example. At the turn of the 19th century, railways completely reshaped urban demographics and trade. Similarly, the internet disrupted entire industries—from media to retail.
The above infographic shows how innovation cycles have impacted economies since 1785, and what’s next for the future.
Innovation Cycles: The Six Waves
From the first wave of textiles and water power in the industrial revolution, to the internet in the 1990s, here are the six waves of innovation and their key breakthroughs.
First Wave | Second Wave | Third Wave | Fourth Wave | Fifth Wave | Sixth Wave |
---|---|---|---|---|---|
Water Power Textiles Iron | Steam Rail Steel | Electricity Chemicals Internal-Combustion Engine | Petrochemicals Electronics Aviation | Digital Network Software New Media | Digitization (AI, IoT, AV, Robots & Drones) Clean Tech |
60 years | 55 years | 50 years | 40 years | 30 years | 25 years |
Source: Edelsen Institute, Detlef Reis
During the first wave of the Industrial Revolution, water power was instrumental in manufacturing paper, textiles, and iron goods. Unlike the mills of the past, full-sized dams fed turbines through complex belt systems. Advances in textiles brought the first factory, and cities expanded around them.
With the second wave, between about 1845 and 1900, came significant rail, steam, and steel advancements. The rail industry alone affected countless industries, from iron and oil to steel and copper. In turn, great railway monopolies were formed.
The emergence of electricity powering light and telephone communication through the third wave dominated the first half of the 1900s. Henry Ford introduced the Model T, and the assembly line transformed the auto industry. Automobiles became closely linked with the expansion of the American metropolis. Later, in the fourth wave, aviation revolutionized travel.
After the internet emerged by the early 1990s, barriers to information were upended. New media changed political discourse, news cycles, and communication in the fifth wave. The internet ushered in a new frontier of globalization, a borderless landscape of digital information flows.
Market Power
To the economist Schumpeter, technological innovations boosted economic growth and improved living standards.
However, these disruptors can also have a tendency to lead to monopolies. Especially during a cycle’s upswing, the strongest players realize wide margins, establish moats, and fend off rivals. Typically, these cycles begin when the innovations become of general use.
Of course, this can be seen today—never has the world been so closely connected. Information is more centralized than it has ever been, with Big Tech dominating global search traffic, social networks, and advertising.
Like the Big Tech behemoths of today, the rail industry had the power to control prices and push out competitors during the 19th century. At the peak, listed shares of rail companies on the New York Stock Exchange made up 60% of total stock market capitalization.
Waves of Change
As cycle longevity continues to shorten, the fifth wave may have a few years left under its belt.
The sixth wave, marked by artificial intelligence and digitization across information of things (IoT), robotics, and drones, will likely paint an entirely new picture. Namely, the automation of systems, predictive analytics, and data processing could make an impact. In turn, physical goods and services will likely be digitized. The time to complete tasks could shift from hours to even seconds.
At the same time, clean tech could come to the forefront. At the heart of each technological innovation is solving complex problems, and climate concerns are becoming increasingly pressing. Lower costs in solar PV and wind are also predicating efficiency advantages.
AI
Visualizing the Top U.S. States for AI Jobs
Nearly 800,000 AI jobs were posted in the U.S. throughout 2022. View this graphic to see a breakdown by state.

Visualizing the Top U.S. States for AI Jobs
Much ink has been spilled over fears that artificial intelligence (AI) will eliminate jobs in the economy. While some of those fears may be well-founded, red-hot interest in AI innovation is creating new jobs as well.
This graphic visualizes data from Lightcast, a labor market analytics firm, which shows how many AI-related jobs were posted in each state throughout 2022.
In total there were 795,624 AI jobs posted throughout the year, of which 469,925 (59%) were in the top 10. The full tally is included in the table below.
Rank | State | Number of job postings | % of total |
---|---|---|---|
1 | California | 142,154 | 17.9% |
2 | Texas | 66,624 | 8.4% |
3 | New York | 43,899 | 5.5% |
4 | Massachusetts | 34,603 | 4.3% |
5 | Virginia | 34,221 | 4.3% |
6 | Florida | 33,585 | 4.2% |
7 | Illinois | 31,569 | 4.0% |
8 | Washington | 31,284 | 3.9% |
9 | Georgia | 26,620 | 3.3% |
10 | Michigan | 25,366 | 3.2% |
11 | North Carolina | 23,854 | 3.0% |
12 | New Jersey | 23,447 | 2.9% |
13 | Colorado | 20,421 | 2.6% |
14 | Pennsylvania | 20,397 | 2.6% |
15 | Arizona | 19,514 | 2.5% |
16 | Ohio | 19,208 | 2.4% |
17 | Maryland | 16,769 | 2.1% |
18 | Minnesota | 11,808 | 1.5% |
19 | Tennessee | 11,173 | 1.4% |
20 | Missouri | 10,990 | 1.4% |
21 | Oregon | 10,811 | 1.4% |
22 | Washington, D.C. | 9,606 | 1.2% |
23 | Indiana | 9,247 | 1.2% |
24 | Connecticut | 8,960 | 1.1% |
25 | Wisconsin | 8,879 | 1.1% |
26 | Alabama | 7,866 | 1.0% |
27 | Kansas | 7,683 | 1.0% |
28 | Arkansas | 7,247 | 0.9% |
29 | Utah | 6,885 | 0.9% |
30 | Nevada | 6,813 | 0.9% |
31 | Idaho | 6,109 | 0.8% |
32 | Oklahoma | 5,719 | 0.7% |
33 | Iowa | 5,670 | 0.7% |
34 | South Carolina | 4,928 | 0.6% |
35 | Louisiana | 4,806 | 0.6% |
36 | Kentucky | 4,536 | 0.6% |
37 | Nebraska | 4,032 | 0.5% |
38 | Delaware | 3,503 | 0.4% |
39 | New Mexico | 3,357 | 0.4% |
40 | Rhode Island | 2,965 | 0.4% |
41 | New Hampshire | 2,719 | 0.3% |
42 | Hawaii | 2,550 | 0.3% |
43 | Mississippi | 2,548 | 0.3% |
44 | Maine | 2,227 | 0.3% |
45 | South Dakota | 2,195 | 0.3% |
46 | Vermont | 1,571 | 0.2% |
47 | North Dakota | 1,227 | 0.2% |
48 | Alaska | 970 | 0.1% |
49 | West Virginia | 887 | 0.1% |
50 | Montana | 833 | 0.1% |
51 | Wyoming | 769 | 0.1% |
The following chart adds some context to these numbers. It shows how the percentage of AI job postings in some of the top states has changed since 2010.
We can see that California quickly became the primary destination for AI jobs in the early 2010s, presumably as Silicon Valley companies began developing the technology.
California’s share has since declined, with a significant number of jobs seemingly moving to Texas. In fact, many tech companies are relocating to Texas to avoid California’s relatively higher taxes and cost of living.
The 10 Most In-Demand Specialized Skills
Lightcast also captured the top 10 specialized skills that were required for AI-related jobs. These are listed in the table below.
Skill | Frequency (number of postings) | Frequency (% of postings) |
---|---|---|
Python | 296,662 | 37% |
Computer Science | 260,333 | 33% |
SQL | 185,807 | 23% |
Data Analysis | 159,801 | 20% |
Data Science | 157,855 | 20% |
Amazon Web Services | 155,615 | 19% |
Agile Methodology | 152,965 | 19% |
Automation | 138,791 | 17% |
Java | 133,856 | 17% |
Software Engineering | 133,286 | 17% |
If you’re interested in a career that focuses on AI, becoming proficient in Python is likely to be a good first step.
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