IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp18984.html

Can AI Improve Household Welfare in Poorer Countries? Evidence and Measurement Challenges

Author

Listed:
  • Dang, Hai-Anh

    (World Bank)

  • Do, Minh

    (University of Economics and Business, Vietnam National University, Hanoi)

Abstract

Can artificial intelligence (AI) make scarce expertise more widely available in poorer countries and improve household welfare? Can it help measure welfare where surveys are infrequent? This structured critical review examines both questions and finds that the answers depend on the application and setting. Across nine selected evaluations, AI assistance raised output per unit of time by 29% on average, and the average remains positive in every reported sensitivity check. Eight tutoring comparisons give an average gain of 0.21 standard deviations on tests taken without the tool, including in poorer-country schools, but this result is less robust when higher-risk trials are excluded. Business and labor-market effects vary, and we found no qualifying causal study of a generative-AI tool’s effect on household consumption poverty in a poorer country. Measured use rises steeply with national income. AI-based models predict wealth levels more accurately than changes, and their value for targeting depends on the alternative and its cost. The review identifies promising applications for evaluated expansion, proposes a survey module, and sets out conditions for validating AI-based statistics and for assessing costs, persistence, and equity.

Suggested Citation

  • Dang, Hai-Anh & Do, Minh, 2026. "Can AI Improve Household Welfare in Poorer Countries? Evidence and Measurement Challenges," IZA Discussion Papers 18984, IZA Network @ LISER.
  • Handle: RePEc:iza:izadps:dp18984
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp18984.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp18984. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mark Fallak (email available below). General contact details of provider: https://edirc.repec.org/data/izaaalu.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.