Compensating for declining workforce with new technologies

Problem

Lithuanian society is among the fastest-aging populations in Europe. Population aging poses a significant challenge for society, and the country’s labour market has not previously faced such a decline in the workforce. According to Eurostat projections, by 2045 nearly half of Lithuania’s population will be 65 years or older, and by 2065 Lithuania will become the oldest society in Europe, with 67.8 people aged 65 and over per 100 people aged 15–64. This means that during this period, the number of working-age residents in Lithuania will decrease by 40%, prompting the need to seek additional productivity resources. 

According to the calculations of the Organization for Economic Co-operation and Development (OECD), approximately 11% of jobs in Lithuania are classified as having a high risk of automation, and artificial intelligence (AI) will affect around 70% of jobs in the future, with 40% of positions expected to see a more than twofold increase in task execution speed. OECD and some researchers estimate that AI has the potential to increase productivity by over 44% over a 20-year period. 

Considering the data, it can be assumed that technology-driven automation has the potential to compensate for the shrinking workforce, enhance current productivity, and thus contribute to the creation of societal well-being, even as the number of employees declines. 

To mitigate the impact of the declining working-age population on the labour market, it is first necessary to assess which jobs or skills could be automated, in which professional areas the workforce is aging the fastest, the relationship between automation and these areas, the correlation between automation and the professions with the fastest aging workforce, and which best practices are applied by the world’s most advanced countries. With this information, we will be able to identify the public policy and monitoring measures that need to be implemented now. 

Goal

The aim of the project is to propose potential solutions for compensating the declining workforce through new technologies.

Participants

2024/25

Viktorija Štarevičiūtė