Millennials are at lower risk of having their jobs automated out of existence than older generations, according to research from Indeed.
The analysis, which compared the online search patterns of millions of UK jobseekers over the six months leading to March, found that younger people are substantially more likely to choose roles at lower risk of automation. While nearly half (48%) of Millennials (those aged between 20 and 36) were searching for what economists term ‘non-routine’ roles, 61% of Baby Boomers (those aged between 53 and 71) were looking for ‘routine’ jobs.
Routine jobs, which include roles in administration, sales and construction, are at a higher risk of automation than non-routine, such as management, professional and service positions. This is because of the higher levels of repetition in routine roles, which machines can master more easily than jobs that require human interaction.
More than a third (34%) of searches by Baby Boomers were for routine manual jobs compared to a fifth ( 20%) of Millennials, making them 67% less likely to be searching for such occupations.
By contrast 30% of Millennials were found to be searching for non-routine, cognitive work such as management and professional roles, compared to just 22% of Baby Boomers.
Mariano Mamertino, EMEA economist at Indeed, pointed out, however, that the automation trend may not be as dramatic as some predict, with time for people of all generations to re-skill. “Automation in the workplace is understandably a sensitive subject for many people,” he said. “Technology continues to reshape not just the way we work but also the number and type of jobs that are available. No generation of jobseekers is completely doomed. Automation is a process not a single event, and technological progress is going to affect different occupations at different times.
“Disappearing jobs can be a frightening concept and it’s impossible to know exactly which jobs are ‘safe’ — but everyone can prepare for the future by building up transferable, non-routine skills that can be applied across a wide array of occupations.”