Machines to do most work by 2025

Joshua Bennett
September 22, 2018

Most workplace tasks have an element of repetitiveness in them which automation systems, in conjunction with agile robotics will be able to perform. The World Economic Forum estimates that machines will be responsible for 52 percent of the division of labor as share of hours within seven years, up from just 29 percent today. However, in terms of overall numbers of new jobs, the outlook is positive.

Simultaneously, rapid changes in machines and algorithms, or computer processes that are designed to solve problems, "could create 133 million new roles in place of 75 million that will be displaced between now and 2022", the group forecast. But it said half of all companies plan to retrain only for "key roles", and only one-third say they plan any retraining for at-risk workers. A major challenge, however, will be training and re-training employees for that new world of work. Many firms may choose to hire temporary workers, freelancers and specialist contractors for tasks not automated by new technology. Respondents represented more than 15 million employees from 20 developed and emerging economies that collectively represent some 70 percent of the global economy. The report said almost half of all companies expect their full-time workforces to shrink by 2022, while almost two in five expect to extend their workforce generally, and over one-quarter expect automation to create new roles in their enterprises.

According to the report, developments of machines and automation software in the workplace could create 58miilion new jobs in the next five years.

George Charles, spokesman for money-saving website, commented: "There's always been the fear with technology, specifically robots, that jobs will be taken over and people will be left without work". The latest edition of the Future of Jobs Report covered over 300 global companies from a wide range of industry sectors. During this implementation period, the person involved develops valuable new skills in AI which can be translated over to other areas where businesses want to use AI and can be used to manage a "team" of AI bots.

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