Human–machine collaboration: exploring professional identity threat within the records and information management community

Purpose This study explores how records and information management (RIM) practitioners perceive threats from artificial intelligence (AI) to their professional identity, and how these perceptions impact their willingness to collaborate with AI-based systems. Design/methodology/approach The research utilized the “AI identity threat framework” to analyse quantitative data from 404 respondents and qualitative data from 21 participants in six Eastern and Southern African countries. Data were analysed using the Structural Equation Modelling technique on IMB-SPSS-AMOS software. Findings AI identity, loss of skills/expertise, changes of work and loss of autonomy significantly predicted professional identity threat (PIT). PIT was found to negatively and significantly predict the intention to use AI-based systems. The proposed moderating variables had no interaction effect. Interviewees affirmed AI as a collaborator, temporal distance, fear of job loss, need for upskilling, shifting roles as predictors of use intention and PIT. Research limitations/implications This study successfully affirmed the existing AI identity threat framework by demonstrating its effectiveness in RIM, identifying new threats and highlighting the varying impact of AI threats across contexts. Originality/value The study findings contribute to the understudied area of AI behavioural use intention within the RIM field and African context.