Purpose The growing disconnect between the near-universal adoption of artificial intelligence (AI) and the more limited results businesses achieve in capturing value from it is, at its core, a people problem, not a technology problem, this paper argues. This study aims to explain how human resources (HR) should be accountable for workforce transformation, which must be closed. Design/methodology/approach Using a conceptual lens, the paper combines recent industry evidence on AI use with the foundations of management thinking, introduces a simple diagnostic to identify where value is going and then puts forward a measurable agenda for action. Findings The analysis breaks down the three interconnected hurdles to value creation with AI: a skills deficit, a lack of re-engineering of human-machine processes and employee scepticism and resistance to implementation. HR is uniquely positioned to address all three, but only by repositioning from a service function to an architect of the human–machine operating model. Practical implications The paper presents four moves HR leaders can make today to create a dynamic skills architecture, redesign jobs to accommodate the human–machine division of labour, proactively manage adoption and build trust in human–AI relationships, as well as three families of metrics to track progress for the board. Originality/value The paper restates the role of AI value capture in HR, not as a technology project, provides a diagnostic to identify where value is lost and offers a set of metrics and actionable steps for senior practitioners to drive the transition.
Singh et al. (Tue,) studied this question.