qainarQainar Journal of Social ScienceQainar Journal of Social Science2958-72122958-7220Q University10.58732/2958-7212-2026-3-131-150qainar-655Research ArticleСтатьиЭкспозиция к искусственному интеллекту и динамика занятости в Казахстане: отраслевой анализArtificial Intelligence Exposure and Employment Dynamics in Kazakhstan: A Sectoral Analysishttps://orcid.org/0009-0001-9702-218XИскаковаГ. К.IskakovaG. K.

PhD, М.Х.

Тараз

Gulzat K. Iskakova – PhD, Associate Professor

Taraz

gk.iskakova@dulaty.kzhttps://orcid.org/0000-0002-0545-4920СарыкуловаЛ. Т.SarykulovaL. T.

к.э.н., доцент

Тараз

Lyalya T. Sarykulova – Cand. Sc. (Econ.), Associate Professor

Taraz

sarykulovalt@gmail.comhttps://orcid.org/0009-0003-0510-508XСарыкуловаЛ. Т.SarykulovaL. T.

к.э.н., доцент

Шымкент

Laura T. Sarykulova – Cand. Sc. (Econ.), Associate Professor

Shymkent

sarykulovalaura539@gmail.comТаразский университет им. М.Х. ДулатиКазахстанTaraz University named after M.Kh. DulatуKazakhstanУниверситет им. Жумабека Ахметулы ТашеневКазахстанUniversity named after Zh.A. TashenevKazakhstan20260610202653131150Copyright © Искакова Г.К., Сарыкулова Л.Т., Сарыкулова Л.Т., 20262026Искакова Г.К., Сарыкулова Л.Т., Сарыкулова Л.Т.Iskakova G.K., Sarykulova L.T., Sarykulova L.T.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.journal-kainar.kz/jour/article/view/655

Быстрое распространение генеративного искусственного интеллекта (далее - ИИ) поставило вопрос о его влиянии на занятость не только в развитых, но и в переходных экономиках. Цель статьи – оценить социальные аспекты трансформации занятости в Казахстане в условиях распространения искусственного интеллекта на основе сопоставления динамики занятости и уровня её формализации в секторах с различной экспозицией к ИИ в 2010–2024 гг. Методология включает отраслевую классификацию экспозиции к ИИ на основе международного индекса AI Industry Exposure, сравнительный анализ динамики занятости, расчёт среднегодовых темпов роста, корреляционный анализ и межгрупповые статистические тесты. Исходную информационную базу составили официальные данные Бюро национальной статистики Республики Казахстан по 17 видам экономической деятельности за 2010–2024 гг. Результаты показали, что за 2010–2024 гг. средний прирост занятости составил 58.5% в секторах с высокой экспозицией к ИИ против 31.1% и 34.7% в секторах со средней и низкой экспозицией соответственно. После 2022 г. среднегодовой темп роста занятости в секторах высокой экспозиции снизился с 3.58% до 1.98%, тогда как в секторах низкой экспозиции увеличился с 1.33% до 2.28%. Связь между уровнем экспозиции к ИИ и изменением темпов роста после 2022 г. оказалась отрицательной и статистически значимой (r=−0.53; p=0.028). Полученные результаты не позволяют установить причинное влияние ИИ на занятость, однако фиксируют различия в отраслевой динамике после начала распространения генеративного ИИ и указывают на необходимость дальнейшего анализа на уровне профессий и трудовых задач.

The rapid spread of generative artificial intelligence (AI) has raised the question of its impact on employment not only in developed but also in transition economies. The purpose of the article is to assess the social aspects of employment transformation in Kazakhstan in the context of the spread of artificial intelligence based on a comparison of employment dynamics and the level of its formalization in sectors with different exposure to AI in 2010-2024. The methodology includes an industry classification of AI exposure based on the international AI Industry Exposure index, a comparative analysis of employment dynamics, calculation of average annual growth rates, correlation analysis and intergroup statistical tests. The initial information base was made up of official data from the Bureau of National Statistics of the Republic of Kazakhstan on 17 types of economic activity for 2010- 2024. The results showed that in 2010-2024, the average employment growth was 58.5% in sectors with high exposure to AI versus 31.1% and 34.7% in sectors with medium and low exposure, respectively. After 2022, the average annual employment growth rate in highexposure sectors decreased from 3.58% to 1.98%, while in lowexposure sectors it increased from 1.33% to 2.28%. The relationship between the level of exposure to AI and the change in growth rates after 2022 turned out to be negative and statistically significant (r=- 0.53; p=0.028). The results obtained do not allow us to establish the causal effect of AI on employment, however, they record differences in industry dynamics after the beginning of the spread of generative AI and indicate the need for further analysis at the level of professions and work tasks.

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The authors declare that there are no conflicts of interest present.