Economy February 27, 2026

Citi Sees AI as a Growing Macroforce but Says Labor Disruption Timing Is Uncertain

Strategists argue policy should skew dovish as implementation frictions and energy limits slow widespread displacement

By Priya Menon
Citi Sees AI as a Growing Macroforce but Says Labor Disruption Timing Is Uncertain

Citi strategists warn that artificial intelligence is likely to become a significant macroeconomic force over time, but emphasize that the timing of material labor-market disruption is highly uncertain. The firm says current labor data show limited broad-based impact, implementation challenges and energy constraints will delay large-scale deployment, and the uncertainty supports a dovish bias for central banks.

Key Points

  • Citi views AI as a likely significant macroeconomic force over time but says the timing of labor-market disruption is very unclear, supporting a dovish policy bias.
  • Current labor data show limited broad-based impact; early career programmers and customer service personal have experienced weakness, while broader indicators suggest the labor market is holding up quite well.
  • Implementation frictions - regulation, corporate adoption challenges and energy constraints - are expected to slow deployment, delaying large-scale displacement; sectors affected include white-collar services, technology providers and energy infrastructure.

Artificial intelligence is poised to be a meaningful driver of macroeconomic outcomes over the long run, but the pace at which it could upend the labor market remains unclear, according to strategists at Citi.

In a Friday note led by Dirk Willer, the team wrote: "While we think that AI may well eventually lead to higher unemployment and deflation, the timing is very unclear." That indeterminacy is central to their policy view, with Citi arguing that the balance of risks is "skewed towards lower Fed Funds, rather than higher ones."


Current labor data and early signs

The strategists say the debate has shifted from whether investment in AI is excessive to how rapidly generative AI could displace white-collar jobs. Despite growing concern after recent advances in generative AI, Citi points to labor-market indicators that do not yet show widespread disruption. In their assessment, the labor market is "holding up quite well."

The note highlights that certain cohorts have experienced weakness: "Essentially, early career programmers and customer service personal have seen a weak job market, but otherwise it is not easy to find much in the data," the strategists said. Beyond these pockets, broad measures of employment and wage pressure have not signaled a clear, economy-wide impact.


Frictions that slow real-world displacement

Citi cautions that several implementation frictions will likely slow the translation of AI capabilities into widescale job substitution. These include regulation, hurdles to corporate adoption and energy constraints. The strategists argue that while AI capabilities themselves might advance exponentially, the path to deployment across companies will be "much more linear," which would push out any macroeconomic effects.

Energy limitations are singled out as a particular bottleneck. At current energy supply levels, the team contends "it would not be possible to replace a significant part of global white-collar work with AI." As long as that bottleneck remains, demand for human labor should persist. They add that over time efficiency improvements and investment in the energy system could alleviate the constraint, but the process will "probably take time."


Longer-term outlook and policy implications

Looking further ahead, Citi sketches a scenario in which substantial productivity gains from AI coexist with job losses and falling prices, particularly if the income benefits from AI accrue mainly to a narrow group they describe as an "AI elite." Under such a scenario, the strategists argue central banks should maintain a dovish bias.

Exposure to potential disruption differs across countries. Citi flags the U.S. and the U.K. as among the developed markets most vulnerable because of their large shares of white-collar service employment. Among emerging markets, Israel, South Korea and parts of central and eastern Europe are identified as relatively more exposed.


This analysis frames AI as a significant structural force that is likely to reshape productivity, prices and employment over time, while stressing that the timing of those changes is uncertain and that near-term labor-market data do not yet reflect broad-based displacement.

Risks

  • Timing uncertainty: The note emphasizes that while AI could eventually raise unemployment and cause deflation, the timing of such effects is highly uncertain, complicating policy and investment decisions.
  • Energy constraints: With current supply levels, Citi argues it would not be possible to replace a significant portion of global white-collar work with AI, making energy availability a key limiter to adoption that affects technology and utility sectors.
  • Implementation frictions and regulation: Corporate adoption hurdles and potential regulatory barriers could slow deployment of AI across firms, delaying macro effects and affecting corporate capital spending and productivity gains.

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