For years, business in the United States has been seen as part of the belief that cloud computing and artificial intelligence are driving wealth-generating productivity. This belief sparked a flood of venture capital funding and corporate spending. Proponents argue that the reward will not be limited to a small group of tech giants, but will extend to the economy as a whole.
This hasn’t happened yet.
The government reported this month that productivity, defined as the cost of goods and services produced per hour of work, fell sharply in the first quarter of this year. Quarterly numbers fluctuate frequently, but they appear to have shattered earlier expectations that a productivity renaissance is finally underway, helped by accelerating digital investment during the pandemic.
Productivity growth since the start of the pandemic is now around 1% per year, a small percentage since 2010, most recently from 1996 to 2004 when productivity grew by more than 3% per year. This is well below the strong improvement.
The economy is growing in addition to capital and labor growth. Another key factor is the country’s ability to create and sell innovations that increase investment and productivity.
A small percentage increase in productivity can make a big difference to a country’s well-being and standard of living over time. McKinney & Company estimates in a report last year that an additional 1% increase in labor productivity in the years to 2024 would increase Americans’ per capita income by $3,500. An average annual growth of 3.8% between 1948 and 1972 was the engine of the country’s post-war prosperity.
Productivity is not a cure, everything is a cure for financial disease. Laura D’Andrea, professor at UC Berkeley’s Haas School of Business, said: Chair of the Clinton administration’s Economic Advisory Board.
However, a less productive economy is a smaller economy with fewer resources to deal with social problems such as inequality.
Today’s productivity mysteries are the subject of lively debate among economists. Robert J. Gordon, an economist at Northwestern University, is one of the main skeptics. According to him, today’s artificial intelligence is primarily a pattern recognition technology, learning a large number of words, images and numbers. According to Gordon, this achievement is “impressive, but does not change”, as was the case with electric motors and internal combustion engines.
Erik Bryn jolf son, director of the Digital Economics Lab at Stanford University, is the leader of the optimist camp. He admits that he is a little disappointed that the increase in productivity is not yet obvious, but he is convinced that it is only a matter of time.