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Will COVID-19 be the tipping point for the Intelligent Automation of work? A review of the debate and implications for research

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  • Coombs, Crispin

Abstract

As part of the urgent need to respond to the COVID-19 pandemic, governments, healthcare providers, and businesses have looked to applications of Artificial Intelligence (AI) to compensate for the unavailability of human workers. This interest has renewed the debate regarding the use of AI for the automation of work, which has been described as Intelligent Automation (IA). A new dimension to this debate is whether COVID-19 will be the catalyst for higher IA adoption levels. This article reviews arguments in favour of COVID-19 increasing the level of IA adoption and possible counter-arguments. Key arguments in favour of increased IA adoption include consumer preferences changing to favour IA, increasing familiarity of IA technologies, and increased business confidence in IA. Counter-arguments include big data availability and reliability limitations, many tasks still favouring human skills over IA, the narrow capabilities of IA technologies, and a high availability of human workers. The article also discusses the implications of this debate for information management research and practice.

Suggested Citation

  • Coombs, Crispin, 2020. "Will COVID-19 be the tipping point for the Intelligent Automation of work? A review of the debate and implications for research," International Journal of Information Management, Elsevier, vol. 55(C).
    • Handle: RePEc:eee:ininma:v:55:y:2020:i:c:s0268401220310100
    DOI: 10.1016/j.ijinfomgt.2020.102182
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    Citations

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    Cited by:

    1. Chun Song & Lionel J. Beaulieu & Indraneel Kumar & Roberto Gallardo, 2023. "COVID-19-Induced Automation: An Exploratory Study of Critical Occupations," Economic Development Quarterly, , vol. 37(2), pages 183-197, May.
    2. Christou, Prokopis & Hadjielias, Elias & Simillidou, Aspasia & Kvasova, Olga, 2023. "The use of intelligent automation as a form of digital transformation in tourism: Towards a hybrid experiential offering," Journal of Business Research, Elsevier, vol. 155(PB).
    3. Arendt, Lukasz & Gałecka-Burdziak, Ewa & Núñez, Fernando & Pater, Robert & Usabiaga, Carlos, 2023. "Skills requirements across task-content groups in Poland: What online job offers tell us," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    4. van Esch, Patrick & Cui, Yuanyuan (Gina) & Das, Gopal & Jain, Shailendra Pratap & Wirtz, Jochen, 2022. "Tourists and AI: A political ideology perspective," Annals of Tourism Research, Elsevier, vol. 97(C).
    5. Martin Lábaj & Matej Vitáloš, 2024. "COVID-19 and automation: Evidence from European countries," Economics Bulletin, AccessEcon, vol. 44(1), pages 112-121.
    6. Aiguo Yan & Mingtao Yu, 2023. "Board Informal Hierarchy and Digital Transformation: Evidence From Chinese Manufacturing Listed Companies," SAGE Open, , vol. 13(4), pages 21582440231, December.
    7. Pramanik, Paritosh & Jana, Rabin K. & Ghosh, Indranil, 2024. "AI readiness enablers in developed and developing economies: Findings from the XGBoost regression and explainable AI framework," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    8. Maciej Cieślukowski & Przemysław Garsztka & Beata Zyznarska-Dworczak, 2022. "The Impact of Robotification on the Financial Situation of Microenterprises: Evidence from the Financial Services Sector in Poland," Risks, MDPI, vol. 10(2), pages 1-20, February.
    9. Ghobakhloo, Morteza & Asadi, Shahla & Iranmanesh, Mohammad & Foroughi, Behzad & Mubarak, Muhammad Faraz & Yadegaridehkordi, Elaheh, 2023. "Intelligent automation implementation and corporate sustainability performance: The enabling role of corporate social responsibility strategy," Technology in Society, Elsevier, vol. 74(C).
    10. Issa Helmi & Lakkis Hussein & Dakroub Roy & Jaber Jad, 2023. "Examining User Engagement and Experience in Agritech," International Journal of Contemporary Management, Sciendo, vol. 59(2), pages 17-32, June.

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