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

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  • Matthew Bone
  • Eugenia Ehlinger
  • Fabian Stephany

Abstract

Emerging professions in fields like Artificial Intelligence (AI) and sustainability (green jobs) are experiencing labour shortages as industry demand outpaces labour supply. In this context, our study aims to understand whether employers have begun focusing more on individual skills rather than formal qualifications in their recruitment processes. We analysed a large time-series dataset of approximately eleven million online job vacancies in the UK from 2018 to mid-2024, drawing on diverse literature on technological change and labour market signalling. Our findings provide evidence that employers have initiated "skill-based hiring" for AI roles, adopting more flexible hiring practices to expand the available talent pool. From 2018-2023, demand for AI roles grew by 21% as a proportion of all postings (and accelerated into 2024). Simultaneously, mentions of university education requirements for AI roles declined by 15%. Our regression analysis shows that university degrees have a significantly lower wage premium for both AI and green roles. In contrast, AI skills command a wage premium of 23%, exceeding the value of degrees up until the PhD-level (33%). In occupations with high demand for AI skills, the premium for skills is high, and the reward for degrees is relatively low. We recommend leveraging alternative skill-building formats such as apprenticeships, on-the-job training, MOOCs, vocational education and training, micro-certificates, and online bootcamps to fully utilise human capital and address talent shortages.

Suggested Citation

  • Matthew Bone & Eugenia Ehlinger & Fabian Stephany, 2023. "Skills or Degree? The Rise of Skill-Based Hiring for AI and Green Jobs," Papers 2312.11942, arXiv.org, revised Nov 2024.
    • Handle: RePEc:arx:papers:2312.11942
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    1. 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).
    2. 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).
    3. 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.
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    Cited by:

    1. Karina Tessar & Pawel Cichecki & Ooko James Opiyo, 2025. "Perception, Motivation, and Career Alignment: A Study on Trainees’ Attitudes Toward Vocational Training Centers in Tana River County, Kenya," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 1072-1084.

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