Understanding Automation Risk

What Do We Mean by Automation and Risk of Automation?

The automation risk data presented in this report come from analyses conducted as part of our ShiftLabs initiatives in 2018. In our analyses, automation risk describes the technical feasibility of automating part or all of the tasks within a job, using currently available technology. The data on automatic risk come from Burning Glass Technologies, and are derived largely from a well-known 2013 study by Oxford University researchers Carl Benedikt Frey and Michael A. Osborne.¹ To calculate automation risk, Frey and Osborne examined approximately 700 occupations, broke them down into individual tasks, and evaluated the ability of automated systems to perform some or all of the tasks within that occupation.

1. “High risk” occupations are the top quartile of risk, with at least an 85 percent risk of automation for a given occupation.
2. “Medium risk” occupations are in the second quartile of risk, between 50 percent and 85 percent risk of automation for a given occupation.
3. “Low risk” occupations are in the bottom two quartiles, with less than 50 percent risk.

A few key caveats are important to consider when interpreting the data.

First, automation risk level is not a prediction that a specific job will be fully automated. Something that can be automated will not necessarily be automated. A range of legal, logistical, business, financial, political, and social factors could lower the real rate at which businesses and employers adopt technology and automate functions. Moreover, predictions about technology have a relatively high degree of uncertainty.

Second, even jobs at high risk of automation will not all be eliminated. Instead, the nature of many jobs will change—in some cases, dramatically—but will remain recognizable occupations. McKinsey estimates that just 5 percent of jobs will be outright eliminated, but that half of all tasks that workers currently perform could be automated.² The implication of this change is that workers in at-risk occupations will need to continuously upskill—to learn additional career skills to improve one’s chances of keeping one’s current job or finding a new one—in order to keep pace with the changing job requirements.

Finally, even though technology and automation will displace some jobs and change others, new jobs will be created and others will expand. Our analysis does not capture the impact of projected job creation: the number of new jobs created through technology or other means.

For more information about our methodology and data, please see the methodology section of the Indianapolis and Phoenix automation risk reports.³

Notes on the Data

• Automation potential data come from Burning Glass Technologies, derived from Carl Benedikt Frey and Michael A. Osborne’s 2013 study “The Future of Employment: How Susceptible Are Jobs to Computerisation?”⁴
• Data on national averages of women in occupations come from the Bureau of Labor Statistics.
• Data on education levels of employed individuals come from the American Community Survey (ACS) five-year estimates (2011–15).