Analysing Labour-Based Estimates of Automation and Their Implications. A Comparative Approach from an Economic Competitiveness Perspective

Abstract

Given the advent of Industry 4.0 and the importance of labour-based automation in ensuring competitiveness at the firm, regional cluster, or country level, the paper aims to explore, for the first time, the features of several estimates of occupational/labour automation and to assess the potential risks associated with it. A comparative analysis of the most well-established estimates of labour automation, the Occupational Information Network (O*NET) degree of automation estimates and Frey and Osborne’s future probabilities of automation was carried out to see whether, and to what extent, these estimates are compatible. Results show significant distributional differences between them, which are quantified into automation-triggered disruption risks at the occupational level, as current levels of labour automation are, in some cases, well below their future estimates. Work context features were used to derive a typology of occupations, which can explain up to one-third of the current, and up to half of the future levels of labour automation. Finally, we identified which occupations and occupational groups are likely to be affected by the highest risk of automation-induced displacement and estimated the magnitude of different disruption classes. Conclusions are compatible with other economywide assessments of the impact of labour automation on the workforce, thus being valuable inputs for corporate strategy, decision-makers and human resource planners as they address a growing need for quantitative insights useful for adapting the labour force structure, workers’ skills, and the task content of occupations to the competitiveness requirements related to the process of digitization in the Industry 4.0 context.

Keywords

• automation
• jobs
• occupational choice
• technological change
• artificial intelligence
• competitiveness