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Skills or Degree? The Rise of Skill-Based Hiring for AI and Green Jobs

Author

Listed:
  • Eugenia Gonzalez Ehlinger
  • Fabian Stephany

Abstract

For emerging professions, such as jobs in the field of Artificial Intelligence (AI) or sustainability (green), labour supply does not meet industry demand. In this scenario of labour shortages, our work aims to understand whether employers have started focusing on individual skills rather than on formal qualifications in their recruiting. By analysing a large time series dataset of around one million online job vacancies between 2019 and 2022 from the UK and drawing on diverse literature on technological change and labour market signalling, we provide evidence that employers have started so-called “skill-based hiring” for AI and green roles, as more flexible hiring practices allow them to increase the available talent pool. In our observation period the demand for AI roles grew twice as much as average labour demand. At the same time, the mention of university education for AI roles declined by 23%, while AI roles advertise five times as many skills as job postings on average. Our analysis also shows that university degrees no longer show an educational premium for AI roles, while for green positions the educational premium persists. In contrast, AI skills have a wage premium of 16%, similar to having a PhD (17%). Our work recommends making use of alternative skill building formats such as apprenticeships, on-the-job training, MOOCs, vocational education and training, micro-certificates, and online bootcamps to use human capital to its full potential and to tackle talent shortages.

Suggested Citation

  • Eugenia Gonzalez Ehlinger & Fabian Stephany, 2023. "Skills or Degree? The Rise of Skill-Based Hiring for AI and Green Jobs," CESifo Working Paper Series 10817, CESifo.
    • Handle: RePEc:ces:ceswps:_10817
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    References listed on IDEAS

    as
    1. Julie Lassébie & Glenda Quintini, 2022. "What skills and abilities can automation technologies replicate and what does it mean for workers?: New evidence," OECD Social, Employment and Migration Working Papers 282, OECD Publishing.
    2. Leal Filho, Walter & Wall, Tony & Rui Mucova, Serafino Afonso & Nagy, Gustavo J. & Balogun, Abdul-Lateef & Luetz, Johannes M. & Ng, Artie W. & Kovaleva, Marina & Safiul Azam, Fardous Mohammad & Alves,, 2022. "Deploying artificial intelligence for climate change adaptation," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    3. Roger Fouquet & Ralph Hippe, 2022. "Twin Transitions of Decarbonisation and Digitalisation: A Historical Perspective on Energy and Information in European Economies," Working Papers 08-22, Association Française de Cliométrie (AFC).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    future of work; labour markets; skills; education; AI; sustainability;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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