Artificial Intelligence Transforms Employment in Russian Companies
Russian enterprises rank among the world’s top ten leaders in AI adoption. In 2023, nearly one-third of domestic companies reported using artificial intelligence. According to a new study by Larisa Smirnykh, Professor at the HSE Faculty of Economic Sciences, the impact of digitalisation on employment is uneven: while the introduction of AI in small and large enterprises led to a reduction in the number of employees, in medium-sized companies, on the contrary, it contributed to job growth. The article has been published in Voprosy Ekonomiki.
Global experience shows that artificial intelligence is rapidly transforming the labour market. On one hand, it can lead to job cuts; on the other, it significantly boosts productivity. So far, most research in Russia on the effects of AI use has focused on the job vacancy market rather than on companies. Larisa Smirnykh, Professor at the HSE Faculty of Economic Sciences and Deputy Head of the HSE Laboratory for Labour Market Studies, set out to fill this knowledge gap.
Her study is based on data from enterprise surveys conducted in 2022 and 2023 by the Laboratory for Labour Market Studies at the HSE Faculty of Economic Sciences. This two-year dataset allowed the author to assess employment dynamics.
The sample included nearly 1,800 enterprises across seven industries: mining, manufacturing, construction, transport and communications, trade and catering, finance, and business services.
According to the survey, 29% of enterprises in Russia have implemented AI—higher than in the EU (22%), slightly lower than in the United States (33%), and behind global leaders such as India (59%) and Singapore (53%).
The survey findings indicate that artificial intelligence has had a significant impact on company employment levels. On average, enterprises that implemented AI saw a 0.79 percentage point decrease in staff numbers compared to the previous year. However, the effect was not uniform: small and large businesses reduced their staff, while medium-sized companies increased their number of employees. The differences between these groups can be explained by a combination of structural and financial factors.
Large enterprises (with more than 250 employees), typically operating in capital-intensive and mature sectors of the economy such as manufacturing, underwent organisational restructuring and staff optimisation. As a result, their employment levels declined by 2.08 percentage points.
Small businesses (with up to 100 employees) were primarily engaged in trade, finance, and business services. Labour costs accounted for the largest share of their expenses (59%), which motivated employers to adopt AI technologies and reduce the number of employees by 1.26 percentage points.
Medium-sized enterprises often demonstrated stable financial performance and a high level of human capital. They expanded production and business operations, creating new tasks for employees. At the same time, AI complemented skilled labour, and there was a 2.96 percentage point increase in the number of employees.
Larisa Smirnykh
'AI technologies can boost productivity, help reduce costs, and optimise staffing levels, potentially leading to higher profits. However, if a company’s revenue comes primarily from other sources, such as resource rents, this company may have less incentive to adopt AI technologies,' notes Larisa Smirnykh of the HSE Faculty of Economic Sciences.
'The decrease in employment following the introduction of AI technologies reflects an adaptation period during which companies gain experience in their effective use,' she emphasises. In the long term, enterprises may see an increase in employment. 'There is no clear evidence yet that AI technologies cause unemployment; instead, their implementation is accompanied almost simultaneously by two effects: job elimination and job creation,’ Prof. Smirnykh explains.
At the same time, some companies have not yet adopted AI technologies. In Russia, the main reasons for this include a perceived lack of necessity (51%), high costs (30%), and a shortage of qualified personnel (14%).
The technological transformation brought about by AI is less disruptive for society and employees when the institutional environment adapts flexibly to these changes. Continuous training in digital skills should be provided to employees, and large companies need to create opportunities for internal mobility within their workforce. 'At the micro level, opportunities must be consistently provided and maintained to support initiatives and encourage individuals who are open to innovation and learning. This requires educational and informational support from both the government and companies,' says Prof. Smirnykh.
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