A EN CESifo (BIS / Georgetown / Chicago)·Paper·

Will AI Help or Hurt Work and the Economy? What People Around the World Expect (CESifo WP 13006)

A · Strong evidence Independently funded survey of more than 64,000 adults in 32 countries by economists from Purdue, Georgetown, ESMT, NBER and the Bank for International Settlements; descriptive data, not yet peer-reviewed.

Summary based on the full text·Original: about 30 minutes to read

In short

CESifo Working Paper 13006 (September 2026) by Claudia Bruschi, Francesco D'Acunto, Fiorella De Fiore, Damiano Sandri and Michael Weber reports what workers worldwide expect AI to do to their jobs and their economies. Across 32 countries, workers are much more likely to expect AI to help their work than to threaten it. Expected help is highest in less productive economies, while expected threat has no link to national productivity, so the two are separate beliefs rather than opposites.

Key numbers

  • 64,000+adults surveyed in 32 countries, covering about 65% of world population and over 85% of world GDP
  • 42% to 86%range across countries of workers expecting AI to facilitate their work
  • 18% to 46%range across countries of workers expecting AI to threaten their work
  • 18.8%workers who expect both facilitation and threat

As reported by the source.

Read the original on ideas.repec.org

English·Web page·opens ideas.repec.org

What it reports

  • Share of workers expecting AI to facilitate their work ranges from 42% to 86% by country; threat ranges from 18% to 46%.
  • Joint distribution: 47.8% expect facilitation only, 11.2% threat only, 18.8% both, 22.3% neither.
  • More than three quarters of Swiss workers expect facilitation, against less than 45% in Italy and Poland.
  • Threat is relatively high in India and South Africa and relatively low in China, Russia and Brazil; Chinese workers expect more facilitation and less threat than US workers.
  • Expected facilitation falls with country TFP (2023, PPP, US = 1), steeply among emerging markets and flat among advanced economies (Japan at about 0.7 resembles Germany at about 1).
  • Threat is unrelated to TFP and to the World Bank Redundancy Rules Index.
  • Facilitation goes with expected higher growth, employment and household income and lower inflation; threat with weaker employment and higher inflation.
  • Within countries, higher-income workers expect more facilitation and less threat; ICT workers report more facilitation without more threat; finance and insurance report substantially more threat.

How they got it

An AI module in the 2026 Global Subjective Expectations Survey run by the European Expectations Center at ESMT Berlin and the BIS, fielded April-May 2026 through Cint online panels, broadly representative of adults aged 18-70 by age and gender. Employed respondents rated "AI will facilitate my work" and "AI will threaten my work" on five-point scales; 12-month income, unemployment and inflation expectations were asked before the AI module. Analysis uses within-country regressions with demographic and sector controls.

Limits

  • Respondents were given no definition of AI, so countries may be judging different technologies.
  • Online panels under-represent offline populations, which matters most in low-income countries.
  • Employed respondents only, asked about current jobs: the survey does not capture fears about hiring or entry-level jobs, where US evidence shows the first effects.

Why it matters for companies

Multinational employers should not assume one AI change story fits every country: the same rollout will meet optimism in India or Indonesia and more scepticism in Italy or Poland. Because help and threat are separate beliefs, communicating productivity gains does not reduce job anxiety; that needs its own response. Finance and insurance staff report the highest threat, which is relevant for shared-service and finance functions. Trust in institutions moves with expected benefit, so credibility of the people leading the change counts.

Summary based on the full text. Read the original for the full argument and data.Read the original on ideas.repec.org

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