Three sectors of the American economy that are adopting artificial intelligence most actively are demonstrating an impressive leap in productivity. Since the end of 2022, labor efficiency in them has been growing twice as fast as before. However, the rest of the economy has not shown such acceleration — and this is a key signal for the markets.
The analysis is based on official statistics from the U.S. Bureau of Economic Analysis and the Bureau of Labor Statistics. The methodology is built on the real value created by one worker: an industry's output is divided by the number of employed people, which allows genuine productivity growth to be separated from simple headcount expansion.
Curious figures
The leaders in AI adoption turned out to be three sectors: information technology, professional services (consulting, law, accounting) and finance. Together they generate a quarter of U.S. private business output, but concentrate only 15% of all workers.
The productivity dynamics in these industries are impressive: from 2005 to 2022, the indicator grew by 2.2% per year, and since the end of 2022 — by 5% per year. If 2005 is taken as the base of 100, then by mid-2026 the index reached 179. At the previous pace, it would have been only about 159.
The rest of the economy has barely accelerated
All other private industries account for 75% of output and 85% of jobs. Here productivity grew by 0.9% per year until 2022 and by 1.4% afterward. There is a difference, but it is insignificant: by mid-2026 the index stood at 120 — almost exactly on the previous trend line.
Manufacturing, trade, construction, healthcare and other sectors continue to operate at virtually the same pace. The thesis that AI will accelerate the entire U.S. economy, judging by the figures, still looks premature.
What this means for investors
The effect of AI is real, but concentrated in a narrow market segment. It is precisely in IT, professional services and finance that businesses are already doing more with the same number of people, and therefore are able to grow profits faster. For the stocks of these sectors, the acceleration in productivity is a direct plus. For the labor market in them, it is a risk: companies are getting by with a smaller workforce per unit of output.
Cryptalist analysis: The data confirm that the monetization of AI is still selective rather than economy-wide — capital is concentrating in high-margin service sectors, where algorithms replace routine labor fastest. For investors, this is an argument in favor of a differentiated approach: a bet on AI is justified primarily through the securities of companies from the three listed industries, while expectations of an economy-wide "AI boom" in manufacturing and traditional business remain speculative until sustained statistics emerge.