Will COVID-19 be the tipping point for the Intelligent Automation of work? A review of the debate and implications for research. (December 2020)

• Record Type: Journal Article
• Authors: Coombs, Crispin
• Is Part Of: International journal of information management. Volume 55(2020)
• Publication Date: 2020-12
• Subjects: Intelligent Automation -- Artificial Intelligence -- Robotics -- Automation -- Future of work -- COVID-19; Social sciences -- Information services -- Periodicals; Social sciences -- Research -- Periodicals; Information science -- Periodicals; Management information systems -- Periodicals; Knowledge management -- Periodicals; Sciences sociales -- Documentation, Services de -- Périodiques; Sciences sociales -- Recherche -- Périodiques; Sciences de l'information -- Périodiques; Systèmes d'information de gestion -- Périodiques; Information science; Management information systems; Social sciences -- Information services; Social sciences -- Research; Periodicals; Electronic journals; 025.52068
• DOI: 10.1016/j.ijinfomgt.2020.102182
• Languages: English
• ISSNs: 0268-4012

Abstract

Highlights: COVID-19 has renewed the Intelligent Automation (IA) of work debate. Strong arguments for COVID-19 increasing IA adoption levels. Counter-arguments against COVID-19 increasing IA adoption also evident. Implications for information management research and practice discussed. 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.