Most workplace tasks have an element of repetitiveness in them which automation systems, in conjunction with agile robotics will be able to perform.
So it'll be farewell to jobs such as office administrator and driver, and hello to new roles such as drone piloting and remote patient health monitoring.
CNBC reported a statement from a Swiss non-profit organization that said human work is expected to account for an average of 58 percent of total work hours by 2022, down from the current total work hours of 71 percent.
Leaders of companies who have submitted their views through the LinkedIn network estimate that over half of today's workloads can be run by machines by 2025. Many firms may choose to hire temporary workers, freelancers and specialist contractors for tasks not automated by new technology.
Companies expect a significant shift on the frontier between humans and machines when it comes to existing work tasks between 2018 and 2022.
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The report also predicts that robots will carry out up to 52 per cent of jobs. Roles that rely on human skills, like sales, marketing and scientific-based positions, will likely see an increase in demand.
'These net gains are not a foregone conclusion, ' WEF chairman Klaus Schwab said. These transformations, could either lead to a new age of good work, good jobs and improved quality of life for all; or pose the risk of widening skills gaps, greater inequality and broader polarization. "Without proactive approaches, businesses and workers may lose out on the economic potential of the Fourth Industrial Revolution", said Saadia Zahidi, head of the Centre for New Economy and Society at the WEF.
Researchers working on "The Future of Jobs 2018" report surveyed executives from different industries around the world, aiming to get a look at how new technologies, like artificial intelligence, will affect the global labor force.
The OECD instead put the USA figure at about 10% and the UK's at 12% - although it did suggest many more workers would see their tasks changing significantly.
"A lot of these new jobs will be centred around understanding and managing the technology, as the limitations of machine learning means it needs human wisdom to guide it".