A boom in generative artificial intelligence and pandemic-induced workplace shifts will unleash a new era of faster productivity growth across the rich world, economists say, though it could take a decade or more for advanced economies to reap the full benefits.
After surging during the initial stages of the pandemic, The Conference Board, a global business research organisation, said this month that it expected productivity to barely grow this year across mature economies. The board believes this weakness is set to continue over the next decade, citing the rising cost of capital and ongoing economic and geopolitical uncertainty.
The forecasts highlight the challenges facing advanced economies, where the struggle to boost productivity since the financial crisis in 2008 has held back increases in output and wages.
However, economists believe the boom in investment into AI — plus several trends in workplaces that took off during the pandemic — will eventually produce compelling results.
Chad Syverson, a professor at the Chicago Booth School of Business, said there was now a “data-driven case for optimism” on productivity, with AI, the formation of new businesses and people switching jobs all set to yield results.
While productivity growth remained weak on paper, he believed that the pay-off from the recent changes in workplace practices — plus the eventual benefits of AI — would take time to feed through into the numbers.
“Very little of this stuff is plug and play . . . companies have to invest a lot of resources to reconfigure their business model for this new thing,” Syverson said. “New software, regulatory issues, all that stuff has to be figured out. There is a period where the technology is around and you can see the benefits but for lots of reasons . . . productivity goes down.”
John Haltiwanger, professor at the University of Maryland, agreed that AI breakthroughs involving large-language models would eventually boost the economy. The US was, he said, now undergoing a transition similar to that of the late 1980s, when the economist Robert Solow said: “You can see the computer age everywhere but in the productivity statistics.”
The radical shifts brought about by generative AI could eliminate what John Van Reenen, professor at the London School of Economics, described as “a lot of drudgery” in workplace practices, enhancing efficiency and growth in the process.
However, earlier technological leaps have taken decades to deliver meaningful pay-offs in productivity.
“It takes an enormous amount of time for companies to change,” said Nick Bloom, a professor at Stanford University, citing the example of the invention of electric motors in an era when most industrial buildings were configured for water or steam power.
There are already big claims for generative AI’s transformational effects on productivity. A recent paper published by the Brookings Institution — written with assistance from the GPT4 model — cites evidence that it can help coders work at twice their previous speed, halve the time taken to complete certain writing tasks and make call centres 14 per cent more productive.
Investment banks, meanwhile, are encouraging clients to buy into generative AI. Researchers at Morgan Stanley say US productivity is “poised to rebound”, in part because demographic trends, combined with government “friendshoring” policies, will make it harder for multinationals to tap a global pool of cheap labour and force them to automate.
An AI-focused “productivity revolution” could be broader than that seen after the introduction of personal computers, they suggested in a recent note, with sectors such as retail and manufacturing “primed to invest”.
Haltiwanger pointed to a surge in the creation of new companies, much of it driven by the shift from city centres to suburban homeworking hotspots.
Provided these fledgling businesses can weather the rise in US interest rates, and any turbulence in regional banks, the rewards should follow. “Any time you go through a change in the way you’re doing business, spatially as well as in areas of the economy, there is productivity growth down the line,” he said.
Van Reenen was more sceptical that labour shortages would drive innovation. While a smaller pool of workers could change the direction of technological change — as in Japan, where an ageing workforce has spurred investment in robotics — it was likely to also mean fewer new ideas.
The Conference Board also sought to temper what it called the “excitement” surrounding technological breakthroughs.
Bloom, meanwhile, warned that it was hard to predict when the big turning points in productivity would come. “The development of the steam engine, electric engine, personal computer and internet did not generate a measurable impact on productivity within five years. So it is hard to think what will. I include [generative] AI in this.”