The Transformative Power of Artificial Intelligence for Managing Customer Relationships: An Abstract

Abstract

An emergent stream of research examines the narrative patterns surrounding new technologies in order to understand how these influence technology acceptance and predict changes in practice. Centered on the application of Artificial Intelligence (AI) to the management of customer relationships, this study explores how the benefits of AI are framed by business consultants and CRM vendors, speculating about how these narratives will transform relationship management practice. As such, our work addresses the call for more studies examining how practitioner discourse (imagination and vision) shapes technology acceptance, offering a novel alternative to the more rational and conscious processes examined in the extant literature (Nagy & Neff, 2015)

Drawing on affordances theory (Gibson, 1966), we contend that practitioner narratives form part of the environment in which AI is operating and thus have the potential to promote and constrain potential use cases or ‘action possibilities’. We aim to uncover which types of affordance business consultants and vendors offering advice to marketing practitioners associate with AI and the extent to which these affordances differ according to user and organizational characteristics. In so doing, we seek to understand whether the application of AI to CRM is being distracted by fantastical prediction in the manner in which the benefits are being framed. By examining what we term the ‘practitioner hype’ we seek to speculate whether AI will transform the practice of managing customer relationships.

The study finds that consultants articulate predominantly ‘perceived affordances’: those that marketers can readily act upon. Thus, AI benefits are construed as offering scope for so-called ‘hyper-personalization’, for example, which includes the ability to more precisely target and personalize marketing communications, predict (and respond to), at scale, potential customer defections and provide individualized responses to customer queries in real time. Whilst the study did not detect hidden or false affordances, the findings did identify a strand of ‘imagined affordances’ of efficiency and effectiveness (best decision making, best performance), which was associated primarily with CRM vendors.

Our work shows that the sector is very optimistic towards the potential offered by AI and express limited uncertainty. The findings indicate that the proliferation of AI-induced automation has the potential of disrupting traditional management of customer relationships.