This study defines who is at risk of automation and discusses policies to ensure the vulnerable groups are seen. The study of Nedelkoska and Quintini (2018) is taken as the role model: The risk of automation for individuals across OECD countries is calculated by associating the expert assessment conducted by Frey and Osborne (2013) with individuals’ skills used at work collected by PIAAC. The analysis is improved by training the model with different country datasets and including additional skills into the analysis. 14% of the total employment of 33 countries is found to be at significantly high risk of automation. Workers at the highest risk of losing their jobs are more likely to be less-educated, low-income earners who perform unskilled jobs. The risk of automation declines as the level of education increases. Therefore, this study highlights the importance of training and reskilling the risky-groups to cope with the possible adverse effects of technological progress.