One of the biggest questions around AI’s economic impact is how it will affect the labor market. Right now, we see a relatively balanced employment picture in the midst of a strong US growth outlook. But with AI capabilities continuing to improve and AI adoption accelerating, AI-driven labor displacement is one of the most plausible downside risks going forward.
We recently shared our thoughts with our clients on how we’re assessing this risk in the near term. Below, I’ve included an excerpt from that research.
Greg Jensen
Co-Chief Investment Officer, Bridgewater Associates
Assessing AI’s Near-Term Effects on the Labor Market
When we look at the shape of the adoption cycle overall, we think the risk of an escalation in labor displacement from AI this year remains modest. This is because:
- Adoption at the depth that can internally displace labor is still low and, at the sector level, narrow. And while there are pockets where more meaningful adoption has occurred (e.g., information, technology, and professional services), these sectors represent only a small share of total employment.
- Additional adoption is currently constrained by the availability of compute. The massive supply/demand imbalance in compute, which we expect to persist well into next year and beyond, threatens to limit adoption both directly, through rationing, and indirectly, by making usage so costly or model access so unreliable that companies are financially or practically disincentivized to adopt.
- While adoption is threatening some jobs, it is also creating others. Integrating AI into current and future workflows requires qualified talent that many companies lack. We can see this dynamic today in an increase in postings for software engineers, as well as for broader AI-related skills. At the same time, the disruptive potential of AI is fueling new business formation. While many of these new businesses may end up causing job losses at incumbents, for now, they represent a new and incremental source of labor demand.
- Pressures on revenues could serve as catalysts to trigger labor replacement, but these look contained today. Historically, cyclical downturns or industry-specific shocks have played an important role in encouraging firms to use technological gains to grow output without scaling up labor. Today, cyclical conditions are strong, with AI capex itself meaningfully supporting the current economic cycle.
This picture is not without vulnerabilities. The cyclical support could change, especially if the conflict in Iran continues. And there is also risk from the cost pressures created by the investments companies are making to position for AI.
But even if the labor pressures from AI adoption only remain muted in the near term, it would still have important implications for Fed policy and for conditions. The US economy is currently facing a mix of inflationary pressures; absent AI-driven softness, an otherwise balanced labor market is unlikely to provide enough disinflationary respite.
AI Adoption Remains Low and Has Not Yet Driven Labor Displacement
One of the dynamics holding back AI-driven labor displacement is narrow adoption. Although reported adoption across the US economy is accelerating, today less than 20% of US firms report AI usage in any business function over the prior two weeks. The chart below shows data on reported adoption according to the Census Bureau’s Business Trends and Outlook Survey, which we see as the data source that samples the most representative universe of US firms.
This picture of narrow AI adoption is compatible with meaningful displacement only if the firms that are adopting AI choose to realize productivity gains by increasing margins through lower employment rather than by expanding output; the data today suggests firms are netting toward the latter. The same BTOS survey discussed above also asked firms that are using AI how that usage has affected employment over the past six months. More than 90% of firms responded that AI has not had any effect on their employment in that window—itself a data point consistent with no meaningful displacement—but among firms where AI did influence firm behavior, more firms reported that AI usage had increased total employment rather than decreased it.
Structural Shifts in Labor Markets Often Require Painful Catalysts; in the Near Term, These Look Unlikely
Today, outside of an extended or escalated Iran conflict, we see relatively low near-term risk of a shock at the macro or industry level that could catalyze material displacement. In the US, low private sector leverage and an unusual composition of borrowing reduce the risk of a self-reinforcing downturn, as the players doing the borrowing are less likely to pull back due to fluctuations in demand or financial conditions. Healthy cyclical conditions are also driving broad-based demand growth across sectors of the economy.
In the left chart below, we show the share of sectors with positive real sales growth; more than 80% of sectors have seen positive real demand growth over the past year, and that breadth is poised to expand based on consensus estimates. And while we’ve seen AI disruption start to get priced into equity markets, the sectors most vulnerable to AI disruption comprise a small share of total employment. In the chart on the right below, we show the share of total US employment in sectors based on our measure of the vulnerability of their revenues to AI disruption. We find that US employment is concentrated in the sectors of the economy that are relatively resilient, with the most vulnerable sectors (i.e., top quintile) comprising an underweight share of total employment (~15%).
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