Economic Fitness and Complexity (EFC) is the recent economic discipline and methodology we have developed in the past ten years. EFC makes use and develops the modern techniques of data analysis to build economic models based on a scientific methodology inspired by the science of Complex Systems with special attention to quantitative tests to provide a sound scientific framework. It consists of a data based and bottom up approach that considers specific and concrete problems without economic ideologies and it acquires information from the previous growth data of all countries with methods of Complex Networks, Algorithms and Machine Learning. Its main characteristics are the scientific rigor, the precision in the analysis and in the forecasting, transparency and adaptability. According to Bloomberg Views: “New research has demonstrated that the "fitness" technique systematically outperforms standard methods, despite requiring much less data”. Recently we have developed these methodologies to study also the impact of AI on the Job Market. Introducing the concept of Job Fitness, on average we observe an inverse proportionality between Job Fitness and AI impact. However, there are also important outliers which require additional considerations. Stimulated by these observations we have developed a radically different and more scientific approach to estimate these effects. This has led us to reconsider the standard information for the impact of AI on the skills. The common wisdom is based on subjective experts opinion while we have now introduced a new approach based on real Start Up investment, which is more objective and scientific and it leads to important differencies. In general, up to now we have considered mostly the analysis of countries. The present challenge is to extend these methodology also for firms. This requires new data and new concepts.