IDEAS home Printed from https://ideas.repec.org/p/bdc/report/20-r-03.html
   My bibliography  Save this paper

Implications of AI on the Indian Economy

Author

Listed:
  • Rajat Kathuria

    (Indian Council for Research on International Economic Relations (ICRIER))

  • Mansi Kedia

    (Indian Council for Research on International Economic Relations (ICRIER))

  • Sashank Kapilavai

    (Indian Council for Research on International Economic Relations (ICRIER))

Abstract

This report has undertaken a comprehensive study of AI’s potential and implication for India, and estimates that impact of AI on the economy in rather granular details. The results of the econometric study done at the firm level highlight the need for continued focus on building digital capabilities to fully utilise the power of AI / ML, both from efficiency and increase in capability perspective. Early and sustained investment in AI / ML, in both R&D and applications, is much required.

Suggested Citation

  • Rajat Kathuria & Mansi Kedia & Sashank Kapilavai, 2020. "Implications of AI on the Indian Economy," Indian Council for Research on International Economic Relations (ICRIER) Report 20-r-03, Indian Council for Research on International Economic Relations (ICRIER), New Delhi, India.
    • Handle: RePEc:bdc:report:20-r-03
    as

    Download full text from publisher

    File URL: https://icrier.org/pdf/Implications_of_AI_on_the_Indian_Economy.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Elhanan Helpman & Manuel Trajtenberg, 1994. "A Time to Sow and a Time to Reap: Growth Based on General Purpose Technologies," NBER Working Papers 4854, National Bureau of Economic Research, Inc.
    2. William D. Nordhaus, 2021. "Are We Approaching an Economic Singularity? Information Technology and the Future of Economic Growth," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 299-332, January.
    3. Peretto, Pietro F. & Seater, John J., 2013. "Factor-eliminating technical change," Journal of Monetary Economics, Elsevier, vol. 60(4), pages 459-473.
    4. Jovanovic, Boyan & Rousseau, Peter L., 2005. "General Purpose Technologies," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 1, chapter 18, pages 1181-1224, Elsevier.
    5. J. Klinger & J. Mateos-Garcia & K. Stathoulopoulos, 2018. "Deep learning, deep change? Mapping the development of the Artificial Intelligence General Purpose Technology," Papers 1808.06355, arXiv.org.
    6. Mongia, Puran & Schumacher, Katja & Sathaye, Jayant, 2001. "Policy reforms and productivity growth in India's energy intensive industries," Energy Policy, Elsevier, vol. 29(9), pages 715-724, July.
    7. Lipsey, Richard G. & Carlaw, Kenneth I. & Bekar, Clifford T., 2005. "Economic Transformations: General Purpose Technologies and Long-Term Economic Growth," OUP Catalogue, Oxford University Press, number 9780199290895.
    Full references (including those not matched with items on IDEAS)

    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. Kroll, Henning & Berghäuser, Hendrik & Blind, Knut & Neuhäusler, Peter & Scheifele, Fabian & Thielmann, Axel & Wydra, Sven, 2022. "Schlüsseltechnologien," Studien zum deutschen Innovationssystem 7-2022, Expertenkommission Forschung und Innovation (EFI) - Commission of Experts for Research and Innovation, Berlin.
    2. Kerstin Hotte & Taheya Tarannum & Vilhelm Verendel & Lauren Bennett, 2022. "Measuring artificial intelligence: a systematic assessment and implications for governance," Papers 2204.10304, arXiv.org, revised Dec 2024.
    3. Liu, Yong & Du, Jun-liang & Yang, Jin-bi & Qian, Wu-yong & Forrest, Jeffrey Yi-Lin, 2019. "An incentive mechanism for general purpose technologies R&D based on the concept of super-conflict equilibrium: Empirical evidence from nano industrial technology in China," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 185-197.
    4. Kariem Soliman, 2021. "Are Industrial Robots a new GPT? A Panel Study of Nine European Countries with Capital and Quality-adjusted Industrial Robots as Drivers of Labour Productivity Growth," EIIW Discussion paper disbei307, Universitätsbibliothek Wuppertal, University Library.
    5. Harald Edquist & Magnus Henrekson, 2006. "Technological Breakthroughs and Productivity Growth," Research in Economic History, in: Research in Economic History, pages 1-53, Emerald Group Publishing Limited.
    6. Roberto Antonietti & Luca Cattani & Francesca Gambarotto & Giulio Pedrini, 2021. "Education, routine, and complexity-biased Knowledge Enabling Technologies: Evidence from Emilia-Romagna, Italy," Discussion Paper series in Regional Science & Economic Geography 2021-07, Gran Sasso Science Institute, Social Sciences, revised May 2021.
    7. Mark Knell & Simone Vannuccini, 2022. "Tools and concepts for understanding disruptive technological change after Schumpeter," Jena Economics Research Papers 2022-005, Friedrich-Schiller-University Jena.
    8. Jeffrey Ding & Allan Dafoe, 2021. "Engines of Power: Electricity, AI, and General-Purpose Military Transformations," Papers 2106.04338, arXiv.org.
    9. Ekaterina Prytkova, 2021. "ICT's Wide Web: a System-Level Analysis of ICT's Industrial Diffusion with Algorithmic Links," Jena Economics Research Papers 2021-005, Friedrich-Schiller-University Jena.
    10. Coccia, Mario, 2015. "General sources of general purpose technologies in complex societies: Theory of global leadership-driven innovation, warfare and human development," Technology in Society, Elsevier, vol. 42(C), pages 199-226.
    11. Pierre Mohnen & Michael Polder & George van Leeuwen, 2018. "ICT, R&D and Organizational Innovation: Exploring Complementarities in Investment and Production," NBER Working Papers 25044, National Bureau of Economic Research, Inc.
    12. Enrico Santarelli & Jacopo Staccioli & Marco Vivarelli, 2023. "Automation and related technologies: a mapping of the new knowledge base," The Journal of Technology Transfer, Springer, vol. 48(2), pages 779-813, April.
    13. Broadberry Stephen, 2012. "Recent Developments in the Theory of Very Long Run Growth: A Historical Appraisal," Jahrbuch für Wirtschaftsgeschichte / Economic History Yearbook, De Gruyter, vol. 53(1), pages 277-306, May.
    14. Fabio Pieri & Michela Vecchi & Francesco Venturini, 2017. "Modelling the joint impact of R and D and ICT on productivity: A frontier analysis approach," DEM Working Papers 2017/13, Department of Economics and Management.
    15. Monica A. Altamirano & Cees P. van Beers, 2018. "Frugal Innovations in Technological and Institutional Infrastructure: Impact of Mobile Phone Technology on Productivity, Public Service Provision and Inclusiveness," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 30(1), pages 84-107, January.
    16. Дементьев В.Е., 2013. "Структурные Факторы Технологического Развития," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 49(4), pages 33-46, октябрь.
    17. Timothy Bresnahan & Pai-Ling Yin, 2010. "Reallocating innovative resources around growth bottlenecks," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 19(5), pages 1589-1627, October.
    18. Christiaan Hogendorn & Brett Frischmann, 2020. "Infrastructure and general purpose technologies: a technology flow framework," European Journal of Law and Economics, Springer, vol. 50(3), pages 469-488, December.
    19. Antonin Bergeaud & Gilbert Cette & Rémy Lecat, 2018. "The role of production factor quality and technology diffusion in twentieth-century productivity growth," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 12(1), pages 61-97, January.
    20. Tilman Santarius & Johanna Pohl & Steffen Lange, 2020. "Digitalization and the Decoupling Debate: Can ICT Help to Reduce Environmental Impacts While the Economy Keeps Growing?," Sustainability, MDPI, vol. 12(18), pages 1-20, September.

    More about this item

    Keywords

    AI; Machine Learning; GPT; icrier;
    All these keywords.

    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:bdc:report:20-r-03. 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: Chhaya Singh (email available below). General contact details of provider: http://www.icrier.org .

    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.