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Does Size Matter? A Comparative Study on AI’s Influence on Employee Training, Business Efficiency, and Competitive Pressure Cover

Does Size Matter? A Comparative Study on AI’s Influence on Employee Training, Business Efficiency, and Competitive Pressure

Open Access
|Aug 2026

Abstract

Artificial intelligence (AI) is reshaping work organisation, yet firms do not benefit equally because adoption depends on organisational scale, resources and workforce readiness. A key practical problem is that smaller enterprises often lack the resources, infrastructure and skills needed to adopt AI, while larger firms may be better positioned to convert AI into training and efficiency gains. This study therefore examines whether company size is associated with AI-related perceptions and outcomes among private-sector firms in Hungary and Slovakia. Data were collected through a structured questionnaire from 269 private-sector enterprises and classified according to European Union size categories. The data were analysed using descriptive statistics, Pearson Chi-Square tests and Gamma coefficients. The results indicate that larger enterprises are more likely to implement AI, invest in employee upskilling, and achieve efficiency gains. Micro and small firms often face resource constraints, limiting adoption and benefits, while medium-sized firms occupy a middle position. No significant link was found between company size and perceptions of AI-related competitive disadvantage, suggesting that industry factors may play a stronger role. These findings highlight the need for targeted support for smaller firms and strategic workforce alignment in larger ones. The study’s limitations include its exploratory sample size and lack of industry-specific analysis, indicating the need for broader future research.

DOI: https://doi.org/10.15544/mts.2026.22 | Journal eISSN: 2345-0355 | Journal ISSN: 1822-6760
Language: English
Page range: 238 - 249
Submitted on: May 12, 2026
Accepted on: Jun 5, 2026
Published on: Aug 27, 2026
Published by: Vytautas Magnus University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
JEL:

© 2026 Aranka Boros, Klaudia Balázs, Enikő Korcsmáros, published by Vytautas Magnus University
This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 License.