 Efficiency Assessment of the Artificial Intelligence Market: Exploring the LimitsYaroslav Kuzminov () and
Ekaterina Kruchinskaia ()
Foresight and STI Governance, 2025, vol. 19, issue 4, 6-16 Abstract: The development of Artificial Intelligence (AI) is significantly impacting the global economy, transforming corporate strategies and enhancing operational efficiency. This study aims to analyze the relative efficiency of the Generative AI (GenAI) market, considering the market size of chips, servers, and data center infrastructure required for its operation, and comparing these market sizes with the market size of AI solutions. The study hypothesizes that the current AI market, despite its rapid development, is characterized by a catching-up nature compared to the component market and does not yet fully reflect the proportional relationship between the volumes of these markets (the hardware market and the AI solutions market). It is emphasized that the capital expenditures of technology giants on the creation of AI infrastructure have significantly increased, which may require decades to achieve a balance between the size of the hardware market that supports AI and the size of the AI solutions market itself. To assess the efficiency of the AI market, the Data Envelopment Analysis (DEA) methodology is applied, considering «inputs» (the market size of components) and "outputs" (the market size of AI solutions). The results of the DEA analysis of the GenAI market dynamics from 2016 to 2024 reveal a non-linear nature of development, starting in 2021, with a trend reversal and a decrease in efficiency indicators, which confirms the hypothesis of the catching-up nature of AI technologies compared to the component market. It is shown that fluctuations in efficiency begin three years after the deployment of the first large language models, indicating their significance for the demand for hardware, but not yet demonstrating sufficient returns in the form of a comparable growth of the AI solutions market. The limitations of the study are associated with the time interval of analysis (2016-2024) and the composition of the companies included in the analysis, which covers a majority, but not the entire, market. The novelty of the study lies in the application of DEA analysis for a comprehensive assessment of the AI market considering, but divides the component market and the technological solutions market of AI usage. The results obtained provide a critical assessment of the prospects for the development of the AI market and identify an imbalance between the «soft» (technological solutions) and «hard» (components) markets, identifying the potential for more efficient exploration and use of generative models. However, the results require further development in terms of describing the effects in different sectors of the economy. Keywords: artificial intelligence; generative AI; DEA analysis; AI efficiency; AI investments; semiconductors market; AI market; AI Investments; large language models; AI economic impact. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:hig:fsight:v:19:y:2025:i:4:p:6-16 Access Statistics for this article More articles in Foresight and STI Governance from National Research University Higher School of Economics |
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