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The potential of artificial intelligence and advanced robotics to perform tasks once reserved for humans is no longer reserved for spectacular demonstrations by the likes of IBM’s Watson, Rethink Robotics’ Baxter, DeepMind, or Google’s driverless car. Just head to an airport: automated check-in kiosks now dominate many airlines’ ticketing areas. Pilots actively steer aircraft for just three to seven minutes of many flights, with autopilot guiding the rest of the journey. Passport-control processes at some airports can place more emphasis on scanning document barcodes than on observing incoming passengers. Skills needs anticipation becomes the practice that harmonises the labour market via insights into educational policies: in the mid- and long-term horizon, the labour market obtains professionals with competencies relevant for market needs, thus closing skills gaps, because educational institutions had enough time and information to adjust. The problem of identifying future skills needs is becoming more and more acute in the current dynamics of the global economy. To smooth the transition caused by the pace of economic globalisation and environmental degradation, and strengthen their position in the new digital world, governments need to envisage the long-term development of critical sectors of the national economy, or shifting to new ones. Of particular interest are the technology-driven industries, as the focal points concentrating research and development, foreign direct investment, talent and cutting-edge technology. Technology can also partially substitute for labour and thus influence the structure of demand: skill-intensive jobs increase in number, while jobs with routine tasks can be replaced by technology. Middle Skill jobs also face a skills set change caused by changing technologies. Skills are required for R&D and innovation, but also for adopting and adapting technologies (business skills, management skills) and for operating and maintaining technologies.