Adoption of artificial intelligence in the HRM function within the South African telecommunication sector: a quantitative analysis using structural equation modelling

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Introduction: The rapid emergence of the digital workplace has accelerated the integration of artificial intelligence (AI) into human resource management (HRM). However, empirical research on the determinants of AI adoption in organisational contexts remains limited, particularly in emerging economies. This study examines the factors influencing AI adoption in HRM within the South African telecommunications sector. Methods: A quantitative approach was adopted, with data collected from 500 HR managers selected systematically. Structural equation modelling (SEM) was used to test relationships between performance expectancy, effort expectancy, facilitating conditions, attitudes, behavioural intention, and actual AI adoption. Results and discussion: Performance expectancy and effort expectancy significantly and positively influenced attitudes towards AI adoption. Facilitating conditions and attitudes were significant predictors of behavioural intention to use AI technologies. Behavioural intention, in turn, had a strong positive effect on actual AI adoption in the workplace. The findings extend existing literature on technology adoption in HRM, particularly in emerging economy contexts. They underscore the importance of perceived usefulness, ease of use, and organisational support in driving AI adoption. For practitioners, the results highlight the need to strengthen enabling conditions and foster positive attitudes to support the successful implementation of AI-driven HR practices.

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