INTERNATIONAL JOURNAL OF FINANCIAL ECONOMICS (IJEFE)
Vol. 2 No. 6 (2025): JUNE

IMPACT OF AUTOMATION ON EMPLOYMENT IN DEVELOPING VS DEVELOPED COUNTRIES

Loso Judijanto (IPOSS Jakarta, Indonesia)
Hadenan Towpek (Universiti Teknologi Mara Cawangan Sarawak, Malaysia)



Article Info

Publish Date
03 Jun 2025

Abstract

This study aims to analyse and compare the impact of automation on employment in developing and developed countries. The literature review is conducted by examining various scientific literature, reports of international organisations, and secondary data related to changes in the structure of employment due to the adoption of automation technology. The results show that developed countries are generally better prepared for digital transformation thanks to adequate infrastructure, adaptive education systems, and progressive labour policies. Automation in developed countries tends to create new job opportunities in the technology and services sectors, although it still requires an increase in labour skills. In contrast, in developing countries, automation has the potential to cause greater disruption to employment, particularly in labour-intensive and informal sectors, due to limited access to education, training and digital infrastructure. The study concludes that to minimise the negative impacts of automation and maximise the opportunities, developing countries need to accelerate investment in education, digital skills training, and strengthening inclusive labour policies. The findings are expected to serve as a reference for policymakers and stakeholders in formulating adaptive labour strategies in the era of automation.

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Journal Info

Abbrev

IJEFE

Publisher

Subject

Economics, Econometrics & Finance

Description

INTERNATIONAL JOURNAL OF FINANCIAL ECONOMICS (IJEFE) is a scientific journal that publishes articles in the field of Business and finance that contain conceptual ideas in the fields of Economics, Accounting, Management, Business and finance. The scope is Human Resource Management, Marketing ...