AI meets labor market: Exploring the link between automation and skills

•We develop a set of tools for labor market intelligence by applying machine learning techniques to web vacancies on the Italian labor market.•We identify, for each occupation, the different types of skills required by the market.•We construct a taxonomy for skills and map it into the ESCO classification system.•We measure the relevance of soft and hard skills and we analyze their detailed composition.•We show that soft and digital skills are related to the probability of automation of occupations.•We shed light on the complementarity/substitutability of hard and soft skills. This paper develops a set of innovative tools for labor market intelligence by applying machine learning techniques to web vacancies on the Italian labor market. Our approach allows to calculate, for each occupation, the different types of skills required by the market alongside a set of relevant variables such as region, sector, education and level of experience. We construct a taxonomy for skills and map it into the recently developed ESCO classification system. We subsequently develop measures of the relevance of soft and hard skills and we analyze their detailed composition. We apply the dataset constructed to the debate on computerization of work. We show that soft and digital skills are related to the probability of automation of a given occupation and we shed some light on the complementarity/substitutability of hard and soft skills.