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Market Power and Artificial Intelligence Work on Online Labour Markets

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Abstract

We investigate three alternative but complementary indicators of market power on one of the largest online labour markets (OLMs) in Europe: (1) the elasticity of labour demand, (2) the elasticity of labour supply, and (3) the concentration of market shares. We explore how these indicators relate to an exogenous change in platform policy. In the middle of the observation period, the platform made it mandatory for employers to signal the rates they were willing to pay as given by the level of experience required to perform a project, i.e., entry, intermediate or expert level. We find a positive labour supply elasticity ranging between 0.06 and 0.15, which is higher for expert-level projects. We also find that the labour demand elasticity increased while the labour supply elasticity decreased after the policy change. Based on this, we argue that market-designing platform providers can influence the labour demand and supply elasticities on OLMs with the terms and conditions they set for the platform. We also explore the demand for and supply of AI-related labour on the OLM under study. We provide evidence for a significantly higher demand for AI-related labour (ranging from +1.4% to +4.1%) and a significantly lower supply of AI-related labour (ranging from -6.8% to -1.6%) than for other types of labour. We also find that workers on AI projects receive 3.0%-3.2% higher wages than workers on non-AI projects.

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  • DUCH BROWN Nestor & GOMEZ-HERRERA Estrella & MUELLER-LANGER Frank & TOLAN Songul, 2022. "Market Power and Artificial Intelligence Work on Online Labour Markets," JRC Working Papers on Digital Economy 2021-10, Joint Research Centre.
    • Handle: RePEc:ipt:decwpa:202110
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    Cited by:

    1. Teutloff, Ole & Einsiedler, Johanna & Kässi, Otto & Braesemann, Fabian & Mishkin, Pamela & del Rio-Chanona, R. Maria, 2025. "Winners and losers of generative AI: Early Evidence of Shifts in Freelancer Demand," Journal of Economic Behavior & Organization, Elsevier, vol. 235(C).
    2. Armenia, Stefano & Franco, Eduardo & Iandolo, Francesca & Maielli, Giuliano & Vito, Pietro, 2024. "Zooming in and out the landscape: Artificial intelligence and system dynamics in business and management," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    3. Dona Ghosh & Rajarshi Ghosh & Sahana Roy Chowdhury & Boudhayan Ganguly, 2025. "AI-exposure and labour market: a systematic literature review on estimations, validations, and perceptions," Management Review Quarterly, Springer, vol. 75(1), pages 677-704, February.
    4. Jiaming Liu & Hongyang Wang, 2025. "Impact of personal information and reputation system on gig workers’ employment status: an interpretable machine learning-based approach," Journal of Computational Social Science, Springer, vol. 8(3), pages 1-40, August.
    5. Gomez-Herrera, Estrella & Mueller-Langer, Frank, 2024. "Does information disclosure affect the gender gap in bidding behavior? Empirical evidence from a natural experiment on a large online labor platform," Labour Economics, Elsevier, vol. 90(C).
    6. Spencer Bastani & Daniel Waldenström, 2024. "AI, automation and taxation," Chapters, in: Stéphane Carcillo & Stefano Scarpetta (ed.), Handbook on Labour Markets in Transition, chapter 19, pages 354-370, Edward Elgar Publishing.
    7. Xu Huang, 2024. "Dynamics of labor and capital in AI vs. non-AI industries: A two-industry model analysis," PLOS ONE, Public Library of Science, vol. 19(1), pages 1-31, January.
    8. 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).
    9. Rolf, Steven & O'Reilly, Jacqueline & Meryon, Marc, 2022. "Towards privatized social and employment protections in the platform economy? Evidence from the UK courier sector," Research Policy, Elsevier, vol. 51(5).
    10. Saara Hämäläinen & Vaiva Petrikaitė, 2024. "Prediction algorithms in matching platforms," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 78(3), pages 979-1020, November.
    11. Anabela Marques Santos & Francesco Molica & Carlos Torrecilla Salinas, 2024. "EU-funded investment in Artificial Intelligence and regional specialization," GEE Papers 181, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Jul 2024.
    12. Cantarella, Michele & Strozzi, Chiara, 2022. "Piecework and Job Search in the Platform Economy," IZA Discussion Papers 15775, Institute of Labor Economics (IZA).

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    JEL classification:

    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • J40 - Labor and Demographic Economics - - Particular Labor Markets - - - General

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