Will COVID-19 be the tipping point for the intelligent automation of work? A review of the debate and implications for research
Open accessAbstract
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.
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The rapid spread of the COVID-19 virus amongst the human population has increased the focus and momentum amongst decision makers on automation technologies and AI solutions.
“The rapid spread of the COVID-19 virus amongst the human population has increased the focus and momentum amongst decision makers on automation technologies and AI solutions.”
From Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life (2020) · cites this paper as Coombs (2020)
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- Authors
- Coombs, C.
- Affiliations
- Loughborough University (GB)
- Corresponding author
- Coombs, Crispin
- ORCID
- Coombs, Crispin
- Venue
- International Journal of Information Management
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 55
- Pages
- 102182
- ISSN
- 0268-4012 (ISSN-L)
- PMC
- PMC7365646
- OpenAlex
- W3042364026
- Cited by
- 167
- References
- 15
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 16 · 2023: 23 · 2022: 51 · 2021: 54 · 2020: 6
- FWCI
- 21.36
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- International Journal of Information Management (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Figshare (submittedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Robotic Process Automation Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- COVID-19 pandemic, intelligent automation, artificial intelligence adoption, workplace automation, human-AI comparison, information management research
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