Future technological advances will permit an increasing number of tasks traditionally performed by humans to become automated. It seems that, such automation focused primarily on routine tasks, e.g. clerical work, bookkeeping, basic paralegal work and reporting etc. However, with the advent of big data, artificial intelligence (AI), the internet of things and ever-increasing computing power, i.e. the digital revolutions, non-routine tasks are also increasingly likely to become automated. For example, the recent development in robotics and 3D printing allow firms in advanced economies to locate production closer to domestic markets in fully aumomated factories. As a result, the future strongest incentive to automate because of their relatively higher labour costs will be reduced, when production automated will bring the negative influence to dismiss some foolish or low produtive or low skill workers, the owning high automated productive skillful workers will replace the low productive skillful workers in any factories' manufacturing environments. So, technological progress participates to raise quantity of jobs will cause result in significant job losses to low skillful workers. Because future employers will need many high automated productive employees to help them to cooperate with (AI) automated machine to work together efficiently. For example, many proportion of occupations at high risk is greatest in Germany and lowest in Korea, these countries organizations will accept to spend technology investments and education of workers to prepare future automatability manufacturing development successfully.However, future automatability manufacturing development will bring technological unemployment in possible, due to workers need to adjust to the challenge of automation by switching tasks. Thus, preventing technological unemployment, also technological change does not just destroy jobs, but also generates new roles through its effect on productivity and the demand for new technologies. For example, it has been estimated that, for each high tech-job created in the industries, such as computing equipment or electrical machinery, some 4.9 % additional jobs are created for lawyers, taxi, drivers and waites in the local economy ( Moretti, 2011).Therefore, automated will also influence service industries' job nature change, e.g. taxi drivers need to apply (AI) automated machines to assist them to drive their taxis. When the passenger tells the taxi driver where he/she wants to go. Then, the (AI automated machine will follow the GPS road direction map to be indicated how to drive the taxi to go to the destination automatically . So, future taxi driver is one assistance role to assist the (AI) automated driving tool to dominate the (AI) tool to drive the taxi to catch the passenger to arrive the destination safety in the short time in possible. For another example, future restaurant waiters will need (AI) automated machines's assistance to help them to deliver or dispatch any foods and soft drinks to send to the identified eater's table carefully in accurate and efficient service performance way from the kitchen, in especially in the busy time and many people are sitting in the large size restaurant environment. So, future, waiter roles will be the leader, they need to manage or control or supervise the (AI) robotics how to make decisions to arrange to dispatch which foods or soft drinks to the different tables in preference immediately. Also, future law clerks need to supervise or manage the law robotics how to help them to make decisions to do revision or draft or filing legal tasks in preference in order to avoid any typing words are mistaken to type on computers or revised draft in wrong way to assist manual legal clerks' mistaken words are appearanced on any legal documents.