Last November, the McKinsey Global Institute released a study to determine prospective job gains and losses under different scenarios through 2030. The emerging picture indicates a future in which up to 800 million people are in danger of losing their job to a machine or a complex algorithm. While for blue-collar workers advances in technology have always posed a threat, recent developments in artificial intelligence mean that several highly-skilled professionals might need to watch their backs as well.
20 High-Paying White-Collar Jobs in Danger of Automation
In a recent study, office listings platform COMMERCIALCafé focused its research on the highest-paying white-collar jobs in the U.S. Firstly, a list of the top 20 white-collar earners was compiled by ranking professions according to their median income earned over the past 12 months. Then, a formula from University of Oxford economists Carl Benedikt Frey and Michael Osborne, measuring automation probability, was applied. Pink-collar jobs, as well as jobs facing less than 20 percent automation probability were excluded.
It is immediately apparent that compensation and benefits managers, and budget analysts have the most cause to worry about the steady pace of technological advancement in the field of AI. Both professions run high computerizable probability scores, at 96 and 94 percent, respectively. Economists, the highest-earning workers to make the list, and boasting a median $109,000 yearly income, face a 43 percent chance of displacement, while personal financial advisors ― currently a 525,000 employee-strong profession, according to 2017 BLS data ― register a 58 percent automation probability. All this means that at least a portion of the individuals currently employed in these jobs will have to consider retraining at some point in their professional future.
However, before painting too bleak a picture, it’s essential to note that automation does not only render some occupations obsolete, it also creates new tasks that need human attention to detail and decision-making. Employees might find they can transition within their field, using their skills for processes that are beyond the scope, capability or financial viability of automation. So, for instance, budget analysts could switch to a position of marketing analyst or account adviser, whereas computer programmers (48 percent automation probability) could slide into any number of increasingly numerous and diverse tech jobs.
Job Automation’s Uneven Impact on Different Age Groups
For those unable to find a new niche within the field they’ve been working in, the challenge of retraining for a new position is bound to be proportionally greater with age. While a diminished learning ability and brain plasticity in older adults do factor in to the hardships faced by certain workers, there are also societal factors that greatly aggravate the situation. Several big tech companies have been exposed as engaging in discriminatory practices towards older generations, narrowing down targeting in their recruitment campaigns to individuals between the ages of 25 and 36.
A second list by COMMERCIALCafé illustrates the majority age group within each of the most endangered white-collar jobs. Currently, people working as judicial workers and agricultural engineers (the majority of which are aged 55 to 64 years old), as well as budget analysts, compensation and benefits managers, space scientists and economists (most of whom are aged between 45 and 54 years) are most vulnerable to the disproportionate effects of automation.
To find out more about the effect job displacement might have on the U.S. office landscape, as well as getting access to the full data set, read more here.
