AI is more likely to boost productivity first, rather than immediately cause large-scale labor substitution at the macro level

Overview

This report is a macro thematic commentary from Morgan Stanley's Sunday Start | What's Next in Global Macro, focused on the relationship among AI, productivity, and the labor market. The report views AI as the sixth major wave of innovation since the Industrial Revolution and argues that AI is likely to significantly raise productivity over the long term. However, because its development is proceeding faster than previous innovation waves, its business-cycle impact will depend on the speed of technological diffusion, the pace of corporate adoption, the economy's adaptive capacity, and policymakers' response during the transition period.

Core views

The report's core view is that AI should not be understood simply as producing the same output with less labor; it can also be understood as generating more output with the same level of employment. Historical experience shows that major technological waves eliminate some tasks and jobs, but more commonly they reshape the composition of work and ultimately expand labor demand. At present, indicators such as overall employment growth, the unemployment rate, job openings, and quits do not show systemic weakening in high-AI-exposure industries. Productivity improvements in these industries are driven more by faster output growth than by declines in hours worked. The report also emphasizes that the future remains uncertain: AI adoption may compress the adjustment cycle, and if job destruction outpaces job creation, short-term unemployment could rise materially.

Analysis framework

The report evaluates AI's impact through historical analogies, observation of current labor market data, comparisons between industry AI exposure and labor productivity, and a macro policy response framework. The analysis does not focus on determining whether a particular industry or company benefits; rather, it compares the relationship between the speed of technological diffusion and the economy's adaptive capacity, while assessing how demand feedback, wealth effects, new task creation, monetary policy, and fiscal policy can cushion employment shocks.

Methodology notes

• MacroeconomicsInnovation Wave Comparison Framework

  Compare AI with historical waves of innovation such as mechanization, electrification, mass production, automation, and the IT revolution.

  This framework is used to assess how new technologies affect productivity, task structure, and labor demand, emphasizing that historical technology shocks typically both replace some tasks and create new ones and higher output.

• Labor MarketAI Exposure and Industry Productivity Observation

  Compare changes in employment, hours worked, and output between high-AI-exposure and low-AI-exposure industries.

  The report notes that high-AI-exposure industries have already shown stronger labor productivity performance, but this has mainly been driven by output growth rather than reductions in hours worked or employment substitution.

• Policy AnalysisMacro Stabilization Policy Buffer Framework

  Assess the buffering role of monetary and fiscal policy against employment and income shocks during the AI transition.

  If AI leads to cyclical employment slowing and lower inflation, monetary policy may turn stimulative to restore full employment; if monetary policy is constrained, fiscal automatic stabilizers and discretionary policy may also help cushion the income gap.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• AI-related infrastructure and data center capital expenditure

  The physical constraint and investment vehicle for AI diffusion

  Strengths

  Long-term demand comes from enterprise AI adoption, data center construction, and related infrastructure investment; the report mentions expected capital spending of more than $3 trillion during 2025-2028.

  Weaknesses

  Only about one-quarter has been deployed so far, and there is still uncertainty around the pace of construction and absorption capacity.

  Comparison

  Compared with rapid progress at the software layer, physical infrastructure buildout is slower and may become a key bottleneck for the speed of AI diffusion.

  Risks

  Overly rapid capital spending, insufficient utilization, tighter financing conditions, or policy changes could weaken investment returns.

• Labor market and wage inflation

  The core macro transmission channel of the AI shock

  Strengths

  Current data on employment, unemployment, job openings, and quits do not yet show systemic weakening in high-AI-exposure industries.

  Weaknesses

  If AI productivity gains are released rapidly while job creation lags, short-term unemployment could rise.

  Comparison

  Historical innovation waves typically ultimately expand labor demand, but AI is diffusing faster, so the adjustment cycle may be shorter.

  Risks

  Youth unemployment, industry mismatch, slowing wage growth, and unequal income distribution may become focal points for policymakers and markets.

• Interest rates and monetary policy

  Policy response assets when AI changes employment and inflation

  Strengths

  If AI brings disinflation and employment slowing, monetary policy may provide countercyclical support.

  Weaknesses

  If policy space is limited, monetary policy alone may not fully offset income and employment shocks.

  Comparison

  Compared with the structural productivity theme, rate assets more directly reflect changes in cyclical unemployment and the inflation path.

  Risks

  Oil prices, tariffs, supply constraints, or a rebound in inflation expectations could limit central banks' easing room.

Key data

• AI Infrastructure Capital ExpenditureExpected to exceed $3 trillion during 2025-2028The report states that only about one-quarter of capital spending on data centers and related infrastructure has been deployed so far.
• Brazil IPCA-15April expected at 1.00% month-over-monthDriven by food inflation and rising energy prices.
• Chile Policy RateExpected to remain unchanged at 4.50%Inflation risks are more persistent, but financial conditions have improved and expectations remain anchored.
• Hungary Key Policy RateExpected to remain unchanged at 6.25%Despite FX appreciation, the NBH is still expected to maintain patient and cautious guidance.
• US Case-Shiller National Home Price IndexJanuary year-over-year 0.9%, February expected 0.5%Home price growth has slowed significantly from 4.2% a year earlier.
• Brazil BCB Policy DecisionExpected to cut rates by 25 basis points to 14.50%The statement may emphasize that economic activity continues to slow.
• US FOMCExpected to stay on holdStill expected to retain an easing bias, while emphasizing that policy needs to remain patient amid uncertainty.
• China NBS Manufacturing PMIExpected to rise to 50.6Previous reading was 50.4 in March.
• Euro Area GDP1Q26 expected at 0.1% quarter-over-quarterBelow 0.2% in 4Q25.
• US 1Q26 GDPExpected annualized quarter-over-quarter growth of 2.4%Forecast uncertainty is high, affected by factors such as delayed construction data, trade, inventories, and a rebound in government output.
• US ISM ManufacturingApril tracking estimate 52.9Demand and output expansion show resilience, but supply and price uncertainty skew near-term risks to the downside.
• US Light Vehicle SalesMarch expected at a 16.0 million annualized paceBelow February's pace; the oil price shock may weigh on durable goods consumption.

Impact & implications

For macro investing, the report leans in favor of AI's long-term productivity dividend and improvement in potential growth, but warns that employment mismatch, unequal income distribution, and cyclical unemployment risk should not be ignored during the transition. If AI diffusion is rapid and infrastructure buildout continues, productivity improvement may support corporate profits, income, and aggregate demand; but if labor adjustment lags technological adoption, markets may focus more on unemployment, wages, disinflation, and expectations for policy easing.

Risks

• AI adoption may outpace the economy's adaptive capacity, causing job destruction to exceed job creation in the short term.
• Productivity gains may be distributed unevenly, leaving some social groups unable to share equally in the technology dividend.
• If infrastructure construction, corporate process transformation, or policy response lags, the release of AI benefits may fall short of expectations.
• Oil prices, tariffs, supply constraints, and geopolitical uncertainty may disrupt the inflation and policy path.
• Macro data are still at an early stage; the current absence of systemic shocks does not mean more visible employment adjustment will not emerge in the future.

What to watch

• The speed and depth of AI diffusion and adoption within enterprises.
• Changes in employment, hours worked, job openings, quit rates, and labor productivity in high-AI-exposure industries.
• Whether productivity gains come from output growth or labor substitution.
• Deployment progress of capital spending on data centers and related infrastructure.
• The difference between youth unemployment and an overall hiring slowdown.
• Central bank policy responses between employment slowing and inflation risk.
• The extent to which fiscal automatic stabilizers and discretionary policy cushion income gaps.