CONTRIBUTORS
Jeffrey Schulze, CFA
Head of Economic and Market Strategy
Josh Jamner, CFA
Senior Investment Strategy Analyst
Key takeaways
- The ClearBridge Recession Risk Dashboard saw no signal changes this month and alternative data sources for indicators still on pause suggest a continuation of trends consistent with no signal changes; the overall dashboard remains firmly in green expansionary territory.
- While AI is popularly being linked to labor weakness, the latter has been most evident in industries that have the lowest AI adoption rates, suggesting that other dynamics are playing a larger role in slowing the pace of job creation.
- While AI labor fears could lead to higher market volatility, the dual tailwinds of fiscal and monetary policy support should power the US economy and corporate earnings in 2026; we remain firmly in the “buy the dip” camp.
AI less of a labor headwind than believed
The S&P 500 Index saw its first 5% pullback in six months during November, only to recover late in the month and ultimately eke out a +0.2% gain. The benchmark now sits within 1% of its all-time high. This volatility was not entirely unexpected; in recent months, discussion of a market bubble has dominated investor conversations. In our view, the initial November slump appears to have been primarily driven by retail investors de-risking as high-momentum darlings bore the brunt of the selloff. Moving into the new year, we continue to believe that a solid earnings backdrop and upside revisions to EPS estimates should drive markets higher despite the S&P 500 Index trading at a lofty 22.4x forward earnings multiple.
From a fundamental perspective, little appears to have changed in the last month. Although the government shutdown has ended, the flow of government data remains interrupted as various agencies work through backlogs. Since our last update, October data has been released for three of the five missing dashboard indicators—Jobless Claims, Retail Sales and Wage Growth—none of which saw changes from their September readings. However, only Jobless Claims has November data available today, meaning four indicators are still not up to date. Crucially, the rest of the dashboard saw no signal changes this month and alternative data sources suggest a continuation of trends consistent with no individual signal changes. As a result, the overall dashboard signal remains firmly in green expansionary territory (Exhibit 1).
Exhibit 1: ClearBridge Recession Risk Dashboard
Data as of Nov. 30, 2025. Sources: BLS, Federal Reserve, Census Bureau, ISM, BEA, American Chemistry Council, American Trucking Association, Conference Board, Bloomberg, CME, FactSet and Macrobond. *Jobless Claims, Retail Sales and Wage Growth were updated with data that had been delayed by the US government shutdown. “Not Available” reflects data that has not been updated due to the government shutdown. The ClearBridge Recession Risk Dashboard was created in January 2016. References to the signals it would have sent in the years prior to January 2016 are based on how the underlying data was reflected in the component indicators at the time.
With underlying economic activity and corporate earnings holding up, many investors are left questioning what sparked the mid-November stock market pullback. One fear that has come up frequently when talking with clients is the concern that more widespread adoption of artificial intelligence (AI) is weighing on job creation. The proponents of this narrative point to younger workers, whose more limited experience and narrower skillset in theory allows for easier substitution of capital (AI) for labor. The pickup in the unemployment rate for the youngest Americans (16–24 years old) to 10.4% from a low of 6.6% in April 2023 has helped bolster this storyline.
A deeper review of labor data shows that while AI is impacting the jobs market, its influence is much less than is commonly perceived. Pockets of AI-induced labor market weakness do exist in specific industries such as software development and call centers. However, when evaluating job creation and AI adoption by industry, labor weakness has been most evident in industries with the lowest AI adoption rates (Exhibit 2). This suggests that other dynamics—changes in immigration and trade policy, the continued aging of the US population and DOGE-related efforts to shrink the Federal workforce—are playing a larger role than AI in slowing the pace of job creation.
Exhibit 2: Lowest AI Adoption, Weaker Labor
Data as of Sept. 30, 2025, latest available as of Nov. 30, 2025. Source: Wolfe Research, Haver Analytics.
Although AI may not be the leading cause of softer job creation so far, many investors fear the potential for larger AI-induced job cuts in the years to come. While this is certainly possible, job losses stemming from technological progress are typically a feature, not a bug, of the US economy. In fact, this year’s Nobel Prize in Economics was awarded for research into the concept of creative destruction: the process where new innovations replace and make obsolete older ones and how this can drive sustained growth through technological progress. This dynamic is always playing out in the US economy, just to a greater or lesser degree depending on the business cycle.
While this time could be different—AI could be more disruptive than past technological innovations—we believe the evidence thus far points to more fear than fact. Further, job losses from AI are only half the story: the creative destruction process also entails job creation as new businesses and whole industries sprout from the seeds of technological progress. The surge in business formation over the past few years (2025 in particular) suggests that some of tomorrow’s leading corporations may already be in their infancy today (Exhibit 3).
Ultimately, the timing and magnitude of disruption will determine how troublesome AI becomes to the economy. Corporate boards will certainly welcome the prospect of efficiency gains and higher profits, and how quickly new businesses can scale their AI adoption will be key in how seamlessly workers transition to new roles and workflows.
However, this pattern has played out with past technological shifts dating back to the steam engine, and history shows that most job losses in areas impacted by technological developments occur during recessions, not expansions. In times of economic strength, there tends to be more of a slow bleed in routine jobs where technology can more easily substitute for workers. The big shifts have come during broader bouts of economic weakness when harder choices must be made, resulting in more pronounced layoff cycles. The “jobless recovery” of the early/mid 2000s following the tech bubble could be a good parallel for what lies ahead when the current economic cycle eventually culminates (Exhibit 4).
Exhibit 3: US Business Formation on the Rise
Data last updated on Sept. 11, 2025, latest available as of Nov. 30, 2025. Sources: US Census Bureau, Macrobond.
Exhibit 4: Share of Workers Employed in Routine Occupations
Routine occupations are those that entail work that follows well-defined instructions and procedures as opposed to tasks requiring flexibility, creativity and problem-solving. Data as of June 30, 2025, latest available as of Nov. 30, 2025. Source: Jaimovich Siu 2018, Goldman Sachs Investment Research.
Importantly, with the ClearBridge Recession Risk Dashboard continuing to signal expansion in the year ahead, this scenario is not a pressing concern, in our view. Given economic strength and scant evidence of AI driving widespread job losses, we believe that fears of substantial further downside to labor from AI are currently misplaced. While AI labor fears could lead to higher market volatility, the dual tailwinds of fiscal and monetary policy support should power the US economy and corporate earnings in 2026. As a result, we remain firmly in the “buy the dip” camp.
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