Why are employees most susceptible to automation least likely to retrain? Automation risks and inequalities in learning intention, perceived opportunities, and learning participation among employee groups

The rise of intelligent technologies is believed to change job requirements, urging individuals to engage in work-related learning to stay employable. Studies on workers’ learning participation found that employees who are most at risk of automation are least likely to engage in work-related learning. To better understand this paradox, this study investigates to what extent differences in work-related learning for technological adaptation are explained by (a) workers’ actual automation risk, (b) their subjective perception of automation risks, (c) differences in their learning intention, and (d) access to lifelong development opportunities and supportive learning environments. Novel survey data on Dutch employees (N = 1,719) are used. The results based on (generalized) structural equation modeling show that differences in learning between high- and low-risk workers can be explained by workers’ differences in their learning intentions and their (perceived) access to education and supportive learning environments, but not by their subjective perceptions of automation.