The aim of paper is to explore the impact of the adoption of the latest waves of technological artefacts (i.e. the massive adoption of AI, robots and machine learning) upon employment dynamics, addressing how the tasks performed by workers might be affected. Many authors discuss about the future of jobs (WEF 2016) and the changing nature of innovation and work (Brynjolfsson and McAfee 2014; Ford 2015). Frey and Osborne (2017) suggest that around 47% of total US employment is potentially automatable over the next decades. Arntz et al. (2016) estimate the share of jobs at risk of automation for 21 OECD countries, with different results. We suggest a different perspective, to wonder not how many and what kind of jobs could disappear, but (1) what are the potential benefits of the adoption of ICT on employment, (2) if (Italian) labour markets are ready to this and (3) under what conditions. In order to achieve our goals, we implement two complementary approaches. First, we give a picture about knowledge, skills and tasks currently required to pursuit of each profession in Italy and US based, respectively on INAPP and O*NET datastes. In order to analyse the databases we distinct two different variables: (a) the degree of automation/substitution; (b) the degree of digitalization. Second, we apply a dictionary about skills and abilities related to Industry 4.0 based on text mining techniques (Fareri et al. 2017). More precisely, we do implement a principal component analysis in order to pin down different patterns of the impact of the Fourth Industrial Revolution on professions in Italy.