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In my view, advances in artificial intelligence (AI) could alter the macro environment meaningfully by raising both trend growth and expectations of long-term real interest rates, but by how much and when is far less clear. Below I set out an initial framework to help answer those questions within the context of deglobalisation and demographic change.
Generative AI technologies offer the promise of human-like output, with high usability thanks to natural language and a wide range of potential applications.
If successfully implemented, AI-driven automation could boost productivity growth by improving efficiency and freeing up resources for more productive tasks. Such an outcome would be welcome in a world where one of the most prevalent market themes over the past decade has been the fear of secular stagnation, where trend growth and R* (the real interest rate when economies operate at full potential) so low that interest rates cannot fall far enough to stimulate investment.
The lack of data makes it incredibly hard to predict the likely macro impact of AI. Some academic studies (Figure 1) have attempted to do so based on a bottom-up breakdown of automation potential by sector and the speed of adoption of past technological advances. Understandably, the range of estimates about the potential boost to productivity are large and depend on assumptions about the level of task automation, associated structural worker displacement and timeline of adoption.
In summary, these studies estimate that productivity growth could be raised by anywhere between 0.2% and 3%, with obviously very different implications. If we take the average across the six studies, the estimated boost to productivity is as much as 1.5%, while potential trend growth — inferred from the share of labour in production — could increase between 0.1% and 2%, with an average of 1%. Those estimates are very large.
Since the global financial crisis (GFC), we’ve seen a steep decline in real bond yields, mostly because of two forces:
R* over time is highly correlated with the trend in productivity and real GDP growth (Figure 2), so it’s not surprising that the drop in estimates of R* coincided with the steep decrease in productivity post-GFC. Investors believed that R* in developed economies had fallen to zero because of the faltering supply and demand picture driven by factors such as a lack of innovation, ageing populations, falling education standards and unequal income distribution. As a result, central banks struggled to get interest rates down far enough to stimulate spending and investment, which prompted discussions about removing the lower bound on rates and, in some instances, rate cuts into negative territory.
If AI could reverse this downward trend in productivity, the level of interest rates that would have been enough to slow the economy over the past 15 years may no longer be sufficient. Higher rates may go hand in hand with increased valuations of risks assets as these rate rises mostly reflect higher estimates for long-term return on capital. Indeed, there is tentative evidence that markets may already have started to price some expectation that AI will raise productivity and trend growth.
We still have little clarity on the speed of transition, the degree of automation possible and the proportion of jobs that are likely to be displaced. In my view, the two most critical questions that still need answering are:
Another important consideration is that AI is not happening in isolation. In some ways, the incentive to adopt these new technologies is higher because several other structural forces, most notably demographic changes and deglobalisation in high-income countries, are raising the cost of labour and lowering productivity.
1S. Briggs and D. Kodnani, “The potentially large effects of artificial intelligence on economic growth”, Goldman Sachs, March 2023.
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