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Measuring the impact of AI on jobs at the organization level: Lessons from a survey of UK business leaders

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  • Hunt, Wil
  • Sarkar, Sudipa
  • Warhurst, Chris

Abstract

Advances in artificial intelligence (AI) have reignited debates about the impact of technology on the future of work, raising concerns about massive job losses. However, extant evidence is beset by methodological limitations. The majority of studies are either (1) based on modelling predictions, underpinned by subjective judgements or (2) measure the effect of automation technologies more broadly using proxies for AI effects. Analysis of what actually happens in organisations introducing AI-enabled technologies is lacking. This Research Note proposes a third methodology based on the use of bespoke employer surveys. Drawing on a new and unique survey of UK business leaders, it illustrates the utility of this approach through the presentation of descriptive findings on the association between introduction of AI and job creation and destruction within organisations. Directions for future research using this approach are suggested.

Suggested Citation

  • Hunt, Wil & Sarkar, Sudipa & Warhurst, Chris, 2022. "Measuring the impact of AI on jobs at the organization level: Lessons from a survey of UK business leaders," Research Policy, Elsevier, vol. 51(2).
    • Handle: RePEc:eee:respol:v:51:y:2022:i:2:s0048733321002183
    DOI: 10.1016/j.respol.2021.104425
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    References listed on IDEAS

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    3. S nziana-Maria Rindasu & Liliana Ionescu-Feleaga & Bogdan-Stefan onescu & Ioan Dan Topor, 2023. "Digitalisation and Skills Adequacy as Determinants of Innovation for Sustainable Development in EU Countries: A PLS-SEM Approach," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 25(S17), pages 968-968, November.
    4. Goto, Masashi, 2023. "Anticipatory innovation of professional services: The case of auditing and artificial intelligence," Research Policy, Elsevier, vol. 52(8).
    5. Zhengang Zhang & Peilun Li & Liangxiong Huang & Yichen Kang, 2024. "The impact of artificial intelligence on green transformation of manufacturing enterprises: evidence from China," Economic Change and Restructuring, Springer, vol. 57(4), pages 1-36, August.

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