A similar productivity lag occurred with electricity, although the observed lag was shorter than for the steam engine. Although the age of electricity began in the 1880s in the United States, it was not until the 1920s that electrification made breakthroughs that led to a dramatic increase in productivity.4
The paradox of rapid technological progress and moderate productivity was also a feature of the computer revolution, which began in the 1970s with the introduction of the personal computer and the Internet. In 1987, Nobel Prize-winning economist Robert Solow observed that “the computer age is visible everywhere except in productivity statistics.”
At the time, labor productivity growth, measured by real hourly output, had slowed to a disappointing 0.5% annual rate, despite major technological advances. It was not until twenty years later, in the late 1990s and early 2000s, that the paradox was resolved when labor productivity regularly exceeded 2% per year between 1998 and 2005, as computer technologies were spreading more widely throughout the economy.5
Faster speed of diffusion and adoption
We find that even as companies invest in AI – 43% of CEOs have already started investing and 45% plan to do so in the next year, according to the EY CEO Outlook Pulse survey – many they seek quick efficiency gains rather than more fundamental measures. changes to maximize AI’s growth potential. And 90% of organizations are still in the early stages of AI maturity.
There are various potential sources of delay between a technological revolution and its increase in productivity, but three are critical:
- Implementation and diffusion: It takes time for new technologies to be adopted and diffused throughout an economy. Even after a technology is introduced, companies may delay its adoption because of high initial costs, uncertainty about its benefits, or simply because they are waiting to see if even better technologies will emerge.
- Learning and adaptation period: Once technology is adopted, there is a period during which workers and managers must learn to use it effectively: this involves trial and error, training and skill development. good practices.
- Complementary innovations: certain technologies require complementary innovations or infrastructures to be fully effective.6 For example, electric motors required an extensive electrical network, and the advantages of personal computers grew with the widespread use of the Internet.
The notable capabilities and performance of emerging AI tools already represent a big improvement over those introduced a decade ago, such as virtual assistants for mobile phones.
Although widespread increases in productivity will likely occur with some lag, the speed of technology adoption and diffusion has increased from several decades in the 1800s to about 10 years in the computer age.
Faster diffusion and adoption of GenAI could mean that the revival of economic activity will be felt over the next three to five years.
