AI in Contact Centers: Artificial Intelligence and Algorithmic Management in Frontline Service Workplaces

dc.contributor.authorDoellgast, Virginia
dc.contributor.authorO'Brady, Sean
dc.contributor.authorKim, Jeonghun
dc.contributor.authorWalters, Della
dc.date.accessioned2023-11-19T18:19:19Z
dc.date.available2023-11-19T18:19:19Z
dc.date.issued2023
dc.description.abstractContact centers have long been lead innovators in adopting new technologies to restructure jobs and manage workers. Between the 1990s and 2000s, the first wave of digitalization transformed what were then called ‘call centers’ through innovations in call volume tracking, automatic call distribution, and electronic monitoring and performance management. The growth of the internet and fiber-optic digital networks enabled the relocation of jobs far from customers through outsourcing and offshoring. Since the mid-2010s – and accelerating in the early 2020s – a new set of technologies have been transforming contact center jobs. This second digital transformation is based on advances in artificial intelligence (AI), enabled by faster network speeds and cloud computing. A range of new AI-based tools are being used to automate customer service and sales via chatbots and voicebots, to perform a growing range of back-office tasks, and to enable more intensive and tailored forms of remote monitoring, coaching, training, and scheduling. In this report, we summarize initial findings from research on how these AI-based tools are being used in contact centers, and their impacts on work and workers. The study focused on contact centers in the US, Canada, Germany, and Norway. We carried out matched case studies in all four countries, including interviews with managers, worker representatives, and employees. We also conducted matched contact center worker surveys in the US (N=2891) and Canada (N=385) between December 2022 and January 2023. In the US, we conducted a survey in 2017 on a similar sample of contact center workers, with some identical questions – allowing us to also describe changes in average responses between these two time periods.
dc.identifier.urihttps://hdl.handle.net/1813/113706
dc.provenancehttps://hdl.handle.net/1813/112248
dc.publisherCornell University, ILR School
dc.subjectartificial intelligence
dc.subjectalgorhythmic management
dc.subjectcontact centers
dc.titleAI in Contact Centers: Artificial Intelligence and Algorithmic Management in Frontline Service Workplaces
dc.typereport
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