ASYMMETRIC DEMOCRATIZATION: PLATFORM MARKET POWER IN RUSSIA'S AI MARKET

  • A.P. Dimenshtein HSE University, Moscow, Russia
  • D.M. Knatko HSE University, Moscow, Russia
DOI: https://doi.org/10.34680/BENEFICIUM.2026.3(60).68-79

Abstract

This paper examines how the market power of corporate platforms in the Russian artificial intelligence market simultaneously shapes the conditions of access to AI technologies for small and medium-sized enterprises and the conditions of scaling for independent AI startups. The problem stems from a contradiction: the contribution of the platform sector to the economy and the availability of ready-made AI services are both growing, while AI adoption among small organisations remains several times lower than among large ones, and the conditions under which independent supply of AI solutions is reproduced remain unexplored. Existing research treats the two sides in isolation and does not describe them as consequences of a single mechanism, which this study sets out to describe and conceptualise. Four objectives are addressed: describing infrastructure concentration in the Russian AI market; characterising platforms as an access channel for smaller firms; identifying the mechanisms that constrain the scaling of AI startups; and proposing an explanatory model linking the two sides. The methodology is combined: a secondary analysis of statistical and industry data on AI diffusion in Russian business, and a multiple case study based on ten semi-structured in-depth interviews with four groups of participants in the Russian AI ecosystem. The principal result is a configuration termed asymmetric democratization: control over computing infrastructure and its access interfaces widens the mass segment's access to using the technology while narrowing access to producing it. Across the ten cases, platform lock-in is found to have a two-level structure, model-level and infrastructure-level: open language models remove the first but not the second, and corporate accelerator programmes consistently fail to perform their declared scaling function. The results yield recommendations for AI startups, development institutions and regulators, while further research should test the proposed stage model longitudinally and operationalise platform lock-in through switching costs.

Keywords: asymmetric democratization, AI startups, switching costs, small and medium-sized enterprises, platform lock-in, boundary resources, platform market power, coopetition

Funding: the research had no sponsorship (own resources).

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About the Authors

Anastasiia P. Dimenshtein – Graduate Student, HSE University, Moscow, Russia. E-mail: dimenshtein_nast@mail.ru. ORCID 0009-0005-5209-2300.

Dmitrii M. Knatko – Ph.D.; Associate Professor, HSE University, Moscow, Russia. E-mail: dknatko@hse.ru. SPIN RINTS 7964-7116. ORCID 0000-0001-8960-860X. ResearcherID E-3017-2016. Scopus Author ID 35368637300.

For citation: Dimenshtein A.P., Knatko D.M. Asymmetric Democratization: Platform Market Power in Russia's AI Market // BENEFICIUM. 2026. Vol. 3(60). Pp. 68-79. (In Russ.). DOI: 10.34680/BENEFICIUM.2026.3(60).68-79

Published
2026-09-06
Issue
No 3 (2026)
Section
PLATFORM SOLUTIONS AND AI TECHNOLOGIES IN MODERN INDUSTRY MANAGEMENT