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Artificial Intelligence and Firm-level Productivity

Author

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  • Dirk Czarnitzki
  • Gastón P Fernández
  • Christian Rammer

Abstract

Artificial Intelligence (AI) is often regarded as the next general-purpose technology with a rapid, penetrating, and far-reaching use over a broad number of industrial sectors. A main feature of new general-purpose technology is to enable new ways of production that may increase productivity. So far, however, only very few studies investigated likely productivity effects of AI at the firm-level; presumably because of lacking data. We exploit unique survey data on firms’ adoption of AI technology and estimate its productivity effects with a sample of German firms. We employ both a cross-sectional dataset and a panel database. To address the potential endogeneity of AI adoption, we also implement IV estimators. We find positive and significant effects of the use of AI on firm productivity. This finding holds for different measures of AI usage, i.e., an indicator variable of AI adoption, and the intensity with which firms use AI methods in their business processes.

Suggested Citation

  • Dirk Czarnitzki & Gastón P Fernández & Christian Rammer, 2022. "Artificial Intelligence and Firm-level Productivity," Working Papers of Department of Management, Strategy and Innovation, Leuven 690486, KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven.
    • Handle: RePEc:ete:msiper:690486
    Note: paper number MSI_2203
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    Cited by:

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    2. Kristina McElheran & J. Frank Li & Erik Brynjolfsson & Zachary Kroff & Emin Dinlersoz & Lucia S. Foster & Nikolas Zolas, 2023. "AI Adoption in America: Who, What, and Where," NBER Working Papers 31788, National Bureau of Economic Research, Inc.
    3. Wang, Linhui & Cao, Zhanglu & Dong, Zhiqing, 2023. "Are artificial intelligence dividends evenly distributed between profits and wages? Evidence from the private enterprise survey data in China," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 342-356.
    4. Erdsiek, Daniel & Rost, Vincent, 2022. "Datenbewirtschaftung in deutschen Unternehmen: Umfrageergebnisse zu Status-quo und mittelfristigem Ausblick," ZEW Expert Briefs 22-09, ZEW - Leibniz Centre for European Economic Research.
    5. Nora Azima Noordin & Khaled Hussainey & Ahmad Faisal Hayek, 2022. "The Use of Artificial Intelligence and Audit Quality: An Analysis from the Perspectives of External Auditors in the UAE," JRFM, MDPI, vol. 15(8), pages 1-14, July.
    6. Iryna Nyenno & Vyacheslav Truba & Liudmyla Tokarchuk, 2023. "Managerial Future of the Artificial Intelligence," Virtual Economics, The London Academy of Science and Business, vol. 6(2), pages 72-88, June.

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    More about this item

    Keywords

    Artificial Intelligence; Productivity; CIS data;
    All these keywords.

    JEL classification:

    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • 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
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

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