The role of artificial intelligence in bridging the negative effects of an aging workforce on productivity

Debelak, Katja (author), Pevcin, Primož (author)

The age distribution of Europe’s workforce has shifted towards older workers over the past few decades, a process expected to accelerate in the years ahead. This demographic trend presents significant challenges to productivity and economic growth, particularly in the EU-27, where workforce aging is projected to reduce growth in total factor productivity. This paper studies the effect of workforce aging on productivity, identifies the main transmission channels, and examines policies that could mitigate its effects. The main research question is whether the utilization of artificial intelligence is offsetting the negative impact of workforce ageing on total factor productivity. The study employs a mixed-methods approach, including quantitative analysis of Eurostat labor market data and qualitative insights derived from interviews with managers. The results of the empirical analysis suggest that AI adoption positively affects productivity, even in the context of a demographic shift associated with ageing workforce. Findings also indicate that AI can partially offset the productivity decline by automating repetitive tasks, enabling older workers to focus on higher-value activities, and facilitating continuous learning through advanced training systems. Additionally, policies aimed at reskilling older workers, promoting intergenerational knowledge transfer, and investing in AI infrastructure could further ameliorate the effects of workforce aging. To sum up, the implications of the study are that artificial intelligence utilization contributes to productivity enhancements, therefore there is a need for introducing policies that promote its adoption, as well as reskilling and upskilling of workforce to be able to follow the trends.

• Language: English
• Keywords: ageing workforce, EU, artificial intelligence, total factor productivity
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FU - Faculty of Administration
• Publication status: Published
• Publication version: Version of Record
• Publication date: 01.01.2025
• Year: 2025
• Number of pages: Str. 287-302
• Numbering: Vol. 28, no. 2
• PID: 20.500.12556/RUL-177369
• UDC: 331.5:331.101.32:004.8:304.4(4–6EU)
• ISSN on article: 1331-5609
• DOI: 10.2478/zireb-2025-0025
• COBISS.SI-ID: 260829955
• Publication date in RUL: 22.12.2025

Record is a part of a journal

• Title: Zagreb international review of economics & business
• Shortened title: Zagreb int. rev. econ. bus.
• Publisher: Faculty of Economics and Business
• ISSN: 1331-5609
• COBISS.SI-ID: 5488156

Licences

• License: CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
• Link: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Description: The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.

Secondary language

• Language: Slovenian
• Keywords: starejša delovna sila, EU, umetna inteligenca, skupna faktorska produktivnost

Projects

• Funder: ARIS - Slovenian Research and Innovation Agency
• Project number: P5-0093
• Name: Razvoj sistema učinkovite in uspešne javne uprave

• Funder: ARIS - Slovenian Research and Innovation Agency
• Name: Vpliv demografskih sprememb in umetne inteligence na trg dela v javnem sektorju