Published 2025-11-15 | Version v1.0
Working PaperOpenPublished

Single-/Few-Human–AI Firms and Single-/Few-Human–AI–Robot Firms

New Archetypes under the MMC Framework

Description

This working paper introduces Single-/Few-Human–AI Firms (S/F-HAI-F) and Single-/Few-Human–AI–Robot Firms (S/F-HAIR-F) as distinct micro- and mini-scale firm archetypes under the MMC framework. It examines their production functions, capital structures, platform dependencies, sectoral boundaries, risk profiles, evolutionary paths, and implications for firm theory and public policy.

Abstract

Advances in generative AI, multi-agent systems, and automation are enabling a new class of firms in which one or a few humans, supported by AI and sometimes robots, can perform at scales once requiring much larger organizations. This paper introduces two such archetypes within a micro- and mini-scale firm framework (MMC): the Single-/Few-Human–AI Firm and the Single-/Few-Human–AI–Robot Firm. Although legally classified as firms, these entities differ fundamentally from traditional organizations in their production functions, capital structures, and risk profiles. These firms are not merely automated sole proprietorships, but organizational forms in which algorithmic capital functionally substitutes for internal labor hierarchies. S/F-HAI-F is characterized by AI-intensive, cognition-focused production, extreme labor leverage, high fixed and near-zero marginal costs, and strong dependence on digital platforms. S/F-HAIR-F extends this model by integrating robotic capital, allowing single- or few-human firms to directly engage in manufacturing, agriculture, logistics, and other physical sectors through micro-scale, automated operations. The paper compares these two archetypes and argues that they represent distinct, path-dependent trajectories rather than stages of a single evolution. The analysis shows that existing firm theories remain applicable but must be extended to account for algorithmic and robotic capital, platform governance, and minimal human headcount. The paper concludes by outlining key implications for firm theory and public policy, including taxation, regulation, and workforce transformation in an economy increasingly shaped by human–AI–robot micro-firms.

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Keywords

  • Single-/Few-Human–AI Firm
  • Single-/Few-Human–AI–Robot Firm
  • S/F-HAI-F
  • S/F-HAIR-F
  • MMC framework
  • Micro- and mini-scale firms
  • Human–AI collaboration
  • Human–AI–robot collaboration
  • Algorithmic capital
  • Robotic capital
  • Platform governance
  • Firm theory
  • Production function
  • Automation
  • Generative AI
  • Multi-agent systems
  • Labor leverage
  • Microeconomic units

Subjects

  • Artificial Intelligence
  • Firm Theory
  • Microeconomics
  • Platform Governance
  • Robotics and Automation
  • Future of Work
  • Human-AI-Robot Systems
  • MMC Framework

Recommended citation

Wu, Shaoyuan. (2025). Single-/Few-Human–AI Firms and Single-/Few-Human–AI–Robot Firms: New Archetypes under the MMC Framework. Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.5281/zenodo.18088667. DOI: To be assigned after Crossref membership approval.

APA citation

Wu, S. (2025). Single-/few-human–AI firms and single-/few-human–AI–robot firms: New archetypes under the MMC framework. Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.5281/zenodo.18088667. DOI: To be assigned after Crossref membership approval.

Alternate identifiers

SchemeIdentifierDescription
DOI10.5281/zenodo.18088667Zenodo/DataCite DOI from early ORCID-derived metadata record
ORCID put-code201017750ORCID public API put-code from early metadata record
File nameSFHAF and SFHARF New Archetypes under the MMC Framework.pdfSource PDF file name
Publication date2025-11-15Date shown in the PDF title page

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References

  1. Acemoglu, D., & Restrepo, P. (2020). Artificial intelligence and jobs. Journal of Economic Perspectives, 34(3), 30–50. https://doi.org/10.1257/jep.34.3.30
  2. Autor, D. H. (2015). Why are there still so many jobs? The history and future of workplace automation. Journal of Economic Perspectives, 29(3), 3–30. https://doi.org/10.1257/jep.29.3.3
  3. Coase, R. H. (1937). The nature of the firm. Economica, 4(16), 386–405. https://doi.org/10.1111/j.1468-0335.1937.tb00002.x
  4. European Commission. (2024). Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). https://eur-lex.europa.eu
  5. Grossman, S. J., & Hart, O. D. (1986). The costs and benefits of ownership: A theory of vertical and lateral integration. Journal of Political Economy, 94(4), 691–719. https://doi.org/10.1086/261404
  6. Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at work: The new contested terrain of control. Academy of Management Annals, 14(1), 366–410. https://doi.org/10.5465/annals.2018.0174
  7. OECD. (2023). OECD AI policy observatory: Artificial intelligence, productivity and the future of work. Organisation for Economic Co-operation and Development. https://oecd.ai
  8. Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform revolution: How networked markets are transforming the economy—and how to make them work for you. W. W. Norton & Company.
  9. Rochet, J.-C., & Tirole, J. (2006). Two-sided markets: A progress report. RAND Journal of Economics, 37(3), 645–667. https://doi.org/10.1111/j.1756-2171.2006.tb00036.x
  10. Williamson, O. E. (1985). The economic institutions of capitalism. Free Press.