IDEAS home Printed from https://ideas.repec.org/a/sgh/gosnar/y2025i3p31-46.html

Generative AI and Income Growth: Early Evidence on Global Data

Author

Listed:
  • Francesco Venturini

Abstract

This paper investigates the relationship between artificial intelligence (AI) and global income growth, with a particular focus on the latest emerging category of digital technologies: generative AI (GenAI). GenAI introduces innovative methods for content creation and can assist with both manual and cognitive tasks, potentially transforming productivity, output, and employment dynamics. By analysing patent data from a global sample of countries, this study aims to assess whether GenAI, even in its early stages, exhibits a positive correlation with income growth. Our findings reveal a statistically significant, albeit quantitatively modest, association between GenAI and GDP per capita growth. Specifically, we estimate a growth premium of approximately 0.02 percentage points over a decade for countries adopting this emerging technology domain—reflecting the extensive margin of GenAI innovation. Additionally, when examining the scale of research efforts in this field (the intensive margin), we find that GenAI has contributed between 0.009 and 0.013 percentage points to GDP per capita growth since 2009.

Suggested Citation

  • Francesco Venturini, 2025. "Generative AI and Income Growth: Early Evidence on Global Data," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 31-46.
  • Handle: RePEc:sgh:gosnar:y:2025:i:3:p:31-46
    as

    Download full text from publisher

    File URL: https://gnpje.sgh.waw.pl/pdf-203715-129334
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2021. "The Productivity J-Curve: How Intangibles Complement General Purpose Technologies," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 333-372, January.
    2. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2025. "Generative AI at Work," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(2), pages 889-942.
    3. Alexandra George & Toby Walsh, 2022. "Artificial intelligence is breaking patent law," Nature, Nature, vol. 605(7911), pages 616-618, May.
    4. Anton Korinek, 2023. "Generative AI for Economic Research: Use Cases and Implications for Economists," Journal of Economic Literature, American Economic Association, vol. 61(4), pages 1281-1317, December.
    5. Hanchen Wang & Tianfan Fu & Yuanqi Du & Wenhao Gao & Kexin Huang & Ziming Liu & Payal Chandak & Shengchao Liu & Peter Katwyk & Andreea Deac & Anima Anandkumar & Karianne Bergen & Carla P. Gomes & Shir, 2023. "Scientific discovery in the age of artificial intelligence," Nature, Nature, vol. 620(7972), pages 47-60, August.
    6. Marioni, Larissa da Silva & Rincon-Aznar, Ana & Venturini, Francesco, 2024. "Productivity performance, distance to frontier and AI innovation: Firm-level evidence from Europe," Journal of Economic Behavior & Organization, Elsevier, vol. 228(C).
    7. Hanchen Wang & Tianfan Fu & Yuanqi Du & Wenhao Gao & Kexin Huang & Ziming Liu & Payal Chandak & Shengchao Liu & Peter Katwyk & Andreea Deac & Anima Anandkumar & Karianne Bergen & Carla P. Gomes & Shir, 2023. "Publisher Correction: Scientific discovery in the age of artificial intelligence," Nature, Nature, vol. 621(7978), pages 33-33, September.
    8. Philip Trammell & Anton Korinek, 2023. "Economic Growth under Transformative AI," NBER Working Papers 31815, National Bureau of Economic Research, Inc.
    9. Igna, Ioana & Venturini, Francesco, 2023. "The determinants of AI innovation across European firms," Research Policy, Elsevier, vol. 52(2).
    10. Takashi Inaba & Mariagrazia Squicciarini, 2017. "ICT: A new taxonomy based on the international patent classification," OECD Science, Technology and Industry Working Papers 2017/1, OECD Publishing.
    11. Venturini, Francesco, 2022. "Intelligent technologies and productivity spillovers: Evidence from the Fourth Industrial Revolution," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 220-243.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jakub Growiec, 2025. "GNPJE Special Issue on Economic Impacts of Generative AI," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 1-5.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Minniti, Antonio & Prettner, Klaus & Venturini, Francesco, 2025. "AI innovation and the labor share in European regions," European Economic Review, Elsevier, vol. 177(C).
    2. Marioni, Larissa da Silva & Rincon-Aznar, Ana & Venturini, Francesco, 2024. "Productivity performance, distance to frontier and AI innovation: Firm-level evidence from Europe," Journal of Economic Behavior & Organization, Elsevier, vol. 228(C).
    3. Igna, Ioana & Venturini, Francesco, 2023. "The determinants of AI innovation across European firms," Research Policy, Elsevier, vol. 52(2).
    4. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).
    5. Flavio Calvino & Luca Fontanelli, 2025. "Decoding AI: Nine facts about how firms use artificial intelligence in France," LEM Papers Series 2025/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Damioli, Giacomo & Van Roy, Vincent & Vertesy, Daniel & Vivarelli, Marco, 2025. "Is artificial intelligence leading to a new technological paradigm?," Structural Change and Economic Dynamics, Elsevier, vol. 72(C), pages 347-359.
    7. Flavio Calvino & Luca Fontanelli, 2024. "AI Users Are Not All Alike: The Characteristics of French Firms Buying and Developing AI," CESifo Working Paper Series 11466, CESifo.
    8. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    9. Evangelos Katsamakas & Oleg V. Pavlov & Ryan Saklad, 2024. "Artificial intelligence and the transformation of higher education institutions," Papers 2402.08143, arXiv.org.
    10. Fabian Dvorak & Regina Stumpf & Sebastian Fehrler & Urs Fischbacher, 2024. "Generative AI Triggers Welfare-Reducing Decisions in Humans," Papers 2401.12773, arXiv.org.
    11. Kaishuai Liu & Shuai Liu, 2025. "Advances in Applied Mathematics in Computer Vision," Mathematics, MDPI, vol. 13(19), pages 1-5, September.
    12. Rathi, Sawan & Majumdar, Adrija & Chatterjee, Chirantan, 2024. "Did the COVID-19 pandemic propel usage of AI in pharmaceutical innovation? New evidence from patenting data," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    13. Song Tong & Kai Mao & Zhen Huang & Yukun Zhao & Kaiping Peng, 2024. "Automating psychological hypothesis generation with AI: when large language models meet causal graph," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    14. Chen, Feng & Deng, Hongyu & Zhang, Xiaoying, 2024. "IG-ENT:A innovative ensemble approach for the flow prediction of main steam system in thermal power plant," Energy, Elsevier, vol. 313(C).
    15. Koehler, Maximilian & Sauermann, Henry, 2024. "Algorithmic management in scientific research," Research Policy, Elsevier, vol. 53(4).
    16. Jianfeng Yao & Cancong Zhao & Xuefan Hu & Yingshan Jin & Yanling Li & Liming Cai & Zhuofan Li & Fang Li & Fang Liang, 2025. "A Method for Estimating Tree Growth Potential with Back Propagation Neural Network," Sustainability, MDPI, vol. 17(4), pages 1-15, February.
    17. Pouliakas, Konstantinos & Santangelo, Giulia, 2025. "Are Artificial Intelligence (AI) Skills a Reward or a Gamble? Deconstructing the AI Wage Premium in Europe," IZA Discussion Papers 17607, Institute of Labor Economics (IZA).
    18. Matthias Niggli & Christian Rutzer, 2023. "Digital technologies, technological improvement rates, and innovations “Made in Switzerland”," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-31, December.
    19. Siluo Yang & Longfei Li & Yujie Jin & Qian feng, 2025. "How does social media mention academic papers? Evidence from WeChat in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(8), pages 4621-4665, August.
    20. Giacomo Damioli & Vincent Van Roy & Daniel Vertesy & Marco Vivarelli, 2024. "AI as a new emerging technological paradigm: evidence from global patenting," DISCE - Working Papers del Dipartimento di Politica Economica dipe0038, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

    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:sgh:gosnar:y:2025:i:3:p:31-46. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Grzegorz Konat (email available below). General contact details of provider: https://edirc.repec.org/data/sgwawpl.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.