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Automation on the way for office management?

Bring on the robots, say British office workers

New research from the Office of National Statistics (ONS) has revealed the jobs most likely to be automated, with Legal Secretaries, Office Supervisors and Office Managers all ranking highly.

The study identified over 710,000 jobs in the Square Mile which they said were at risk from new automated technology, with Legal Secretaries at 61.6% likelihood of automation, followed by Office Supervisors (48.7%) and Office Mangers (47.1%).

Young people are most likely to be impacted, with those between 35 and 39 being the least likely to face automation.

However, the overall proportion of risk from robots taking jobs has decreased since the last ONS survey back in 2011, from 8.1% to 7.4%.

And the good news is that the City  is actually a fairly safe zone from robot competition, after Camden, Three Rivers and Oxford.

The analysis studied tasks performed by people in jobs across the whole labour market, assessing the probability that some of these jobs would be more efficient if automated.

Routine and repetitive tasks scored highly on the automation chart, with administrative and secretarial occupations sitting mid-table between 45%-65%. 

Occupations that are considered low-skilled or routine had the highest level of automation risk, such as waiters or waitresses, shelf fillers and elementary sales occupations.

The three occupations at the lowest risk of automation are medical practitioners, higher education teaching professionals and senior professionals of educational establishments, all considered high skilled.

The analysis also revealed that 70.2% of the roles at high risk of automation are currently held by women, with people aged between 20-24 years more likely to be affected than any other age group.

In total, the analysis found that around 1.5 million jobs were considered high risk of automation. 

“It is not so much that robots are taking over, but that routine and repetitive tasks can be carried out more quickly and efficiently by an algorithm written by a human, or a machine designed for one specific function,” the report concluded.