Transitioning to artificial intelligence-based key account management: A critical assessment
Daniel D. Prior, Javier Marcos Cuevas
Abstract
Research suggests that Artificial intelligence (AI) use for sales and marketing activities improves firm performance. Underpinning these AI applications are datasets that reflect large volumes of sales transactions and interactions with a broad range of customers. Conversely, key account relationships involve deep and focused engagements with a small number of strategically important customers at multiple levels, and this has important implications for AI data inputs and uses. Whether AI is appropriate or relevant to key account management (KAM) is currently unclear. In this paper, we critically evaluate AI applications for KAM. The paper highlights the amenability of a firm’s KAM capabilities to AI and evaluates the opportunities and challenges that AI-based KAM offers. The paper also outlines a set of moderating factors likely to affect the impact of AI on KAM and provides a conceptual model to better understand the potentially transformative effects of AI on KAM. The paper concludes with a set of theoretical and managerial implications of AI-based KAM and develops a comprehensive research agenda to contribute to the further exploration of AI-based KAM. • Develops an AI-based KAM capabilities framework that highlights and describes AI implications for KAM. • Describes a series of moderating factors that could impact AI-based KAM. • Outlines a series of theoretical and managerial implications for AI-based KAM. • Develops an extensive research agenda that establishes AI-based KAM as a field of research.