While many of those robots will be used in the automotive and electronics sectors, VisualCapitalist’s Jeff Desjardins notes that there are many other roles that robots will be filling in the future. Surprisingly, according to global consultant McKinsey & Co, not all of these jobs are low-skill, low-wage jobs, either.
Mckinsey ran a comprehensive study of nearly 800 different jobs in the United States, ranging from CEOs to fast food workers. Between these roles, they found 2,000 individual work activities, and assessed them against 18 different capabilities that could potentially be automated. In their analysis, they found that 45% of work activities representing $2 trillion in wages can already by automated based on proven technology that currently exists. A further 13% of work activities in the U.S. economy could be automated if the technologies used to understand and process human language were brought up to the median human level of competence.
(click image for fully interactive version)
WHO’S IN, WHO’S OUT?
The interactive visualization above charts specific careers on their automation potential (out of 100%) along with the hourly average wage of the job.
What is most interesting about the analysis is that automation potential doesn’t correlate with low-skill, low-wage jobs as much as one may think. While it’s true that the three million fast food workers across the country have an automation potential of 74%, and that heavy truck driving activities can be 69% automated, there are also great counter-examples: for example, only 7% of manual labor and 22% of janitorial activities could be automated.
Likewise, high-paying jobs are not necessarily robot-proof.
Doctors (23%), nurses (29%), and even CEOs (25%) all have significant amounts of their jobs that can be automated with current technology. Almost half (47%) of what pharmacists do can be done by a robo-pharmacist, and 72% of commercial pilot activities can be done through computers.
Not interested in having a robot fill your shoes? Mckinsey notes at the end of their analysis that both creativity and sensing emotion are extremely difficult to automate. Focus on building skills and competencies in these categories, and you’ll be just fine (for now, at least).