Future of work

As technologies like AI, robotics, and the internet transform workplaces, skills classification systems must evolve alongside them. This study uses text-mining techniques to evaluate how well the European Skills, Competences, Qualifications and Occupations classification (ESCO) captures emerging skills related to Industry 4.0 technologies. 

Using named entity recognition (a natural language processing technique for identifying the names of people, organizations, locations and more), the researchers analyzed 13,712 scientific papers on Industry 4.0 to identify 752 distinct technologies. They then compared this list against two versions of ESCO (versions 1.0 and 1.1) to assess alignment. Among the top 80 trending technologies identified in the scientific literature, 70% were already included in one of the two ESCO versions, indicating reasonable alignment overall.  

Technologies added in ESCO version 1.1 showed the highest growth rates in scientific publications (an 89.3% relative development of growth rate). This suggests that the ESCO classification system is successfully evolving to reflect emerging technological trends. 

However, the analysis identified notable gaps:  

• Key Industry 4.0 pillars, such as cyber-physical systems, digital twins, and manufacturing execution systems, were absent from ESCO entirely.  

• The classification lacked robotics-related terminology (such as collaborative robots and agent-based models) and network technologies (such as wireless networks, radio frequency identification, and Bluetooth).  

This matters because these omissions could limit ESCO’s usefulness for workers and employers navigating digital transformation. 

This research has direct relevance for Canada’s approach to classifying occupations. Canada’s National Occupational Classification (NOC), which is maintained jointly by Statistics Canada and Employment and Social Development Canada, serves a function that is similar to ESCO’s. The NOC underwent a structural revision in 2021, when the Training, Education, Experience, and Responsibilities (TEER) categorization was introduced to replace the previous skill-level system. Statistics Canada has also developed the Occupational and Skills Information System (OaSIS), which links skills to occupations using a skills and competencies taxonomy.  

The text-mining methodology demonstrated in this study could be applied to evaluate whether Canadian classification systems adequately capture emerging technologies. Given that approximately 60% of Canadian workers are in jobs that may be affected by AI-driven job transformation, it is increasingly urgent to ensure that skills frameworks accurately reflect Industry 4.0 requirements. The NOC is undergoing revisions for the 2026 version. Public consultations closed in November 2024 to gather input on changes that reflect evolving occupations.  

The study also raises important considerations about the granularity of skill classifications. The researchers found that ESCO included specific trade names (such as Android and iOS), but missed more general technology categories. This inconsistency presents challenges for both comprehensiveness and usability.  

For Canadian policy-makers and workforce planners, the findings suggest that automated text analysis of scientific and technical literature could provide valuable signals about emerging skill needs, potentially supplementing traditional methods like employer surveys and expert panels.