The interplay of self-efficacy, artificial intelligence literacy and lifelong learning for career resilience among older employees: a comparison study between China and Malaysia

The ageing global population, combined with rapid technological advancements, has significantly reshaped the labor market in recent decades. As demographic shifts and AI technologies become increasingly ubiquitous, this study aims to investigate older employees’ perceptions of career resilience by analyzing the interplay between self-efficacy, AI literacy, and lifelong learning for job security and employability. A purposive sampling technique using pre-determined criteria was employed to ensure accurate data collection. A quantitative research design was adopted, followed by data analysis through a partial least squares structural equation modeling approach. To gain further insights, a comparative study was conducted between China and Malaysia using multigroup analysis (MGA). The study collected 200 responses from each country, adhering to Roscoe’s (1975) rule-of-thumb requirement. A final total of 400 responses were gathered representing a range of educational backgrounds and worked in various organizational settings. Corresponding direct and indirect hypotheses were developed to meet the research objectives. The predictability of the model was assessed using PLSpredict together with a cross-validated predictive ability test (CVPAT). The results revealed that self-efficacy positively affects AI literacy and lifelong learning, lifelong learning is positively associated with job security and employability, and AI literacy positively influences employability but not job security. Additionally, the study revealed different outcomes between China and Malaysia, which could be attributed to cultural differences and workplace dynamics in these countries. These findings suggest that older employees can enhance their career resilience through self-efficacy, enabling them to acquire new knowledge and skills for adapting to technological change.