The Future of Work

Data, Research, and Insights

How Risk of Job Loss to Automation Declines

One irony of increasing adoption of automation and artificial intelligence is that the share of jobs deemed “at-risk” continues to shrink. That’s because jobs previously in the “at risk” category have shifted to become automated, while emerging jobs require increasingly specialized skills for workers to operate and monitor equipment.

The problem is not necessarily that robots will take over jobs. McKinsey makes it clear that the world’s economy will need every erg of human labor working to overcome demographic aging trends. The problem actually lies in the disappearance of low-skill jobs and greater emphasis on skills that are uniquely human — social-emotional skills, commonly referred to as soft skills.

We can look to other states to yield a probable 20-year trajectory for the rate at which low-skill jobs might be automated in Michigan. Our review of U.S. Bureau of Labor Statistics data shows the declining trend of automation risk in Michigan largely tracks the rest of the country over the 20-year period from 1998 to 2018.

Try selecting and comparing different geographies and occupations to see how automation risk varies over time. Hover over any point on the graph for more information.

What’s interesting is that Michigan had the same level of risk for jobs lost to automation in 1998, at 62 percent, as the level faced in 2018 by the three most at-risk states, Nevada, South Dakota, and Alabama. In other words, three years ago, the states with the most risk were picking up where Michigan left off over 20 years ago.

Michigan’s risk has declined to 57.5 percent as recently as 2018 – nearly identical to the level of risk associated in 1998 with the three most-resistant states. As we approach the level of risk attributed to the lowest-risk states back in 1998, we can look to states like Maryland, Connecticut, and Massachusetts to plot a path forward. This helps identify which jobs will be most resistant to automation so we can determine the best methods to upskill and retrain our workforce in preparation for the impending future of work.


Strong Correlation Between Soft Skills, Salaries, and Automation Risk

Using data from the O*NET database, we can see that occupations that place the greatest importance on soft skills also generally face the lowest risks of being automated and earn the highest average wages.

Try selecting and comparing different soft skills or occupation groups and hover over any bubble in the chart for more information. Then see the summary at the end of this section for some key findings we discovered.

Healthcare and Management occupations are two examples that rank extremely high in soft skills as well as average wages, while also facing the lowest risk from automation. Conversely, occupations in Farming or Production are associated with the highest automation risk, the lowest average salaries, and place the least importance on soft skills.


Tracking the Growth of Soft Skill Importance

Considering how automation risk has declined in Michigan over the past 20 years, it should come as no surprise that the importance placed on soft skills has grown. The interactive below illustrates that in 1999, 36.1 percent of jobs in Michigan and 36.2 percent of jobs in the U.S reported that soft skills were “very important.” As of 2018, that share had risen to 37.0 percent in Michigan and 37.4 percent across the nation.

Try selecting and comparing across different occupation groups, soft skills, and geographies to review the gaps between "very important" vs. "not very important." Hover over any point on the graph for more information. Then see the summary at the end of this section for some key findings we discovered.

Disaggregating this data to isolate specific skills — filtering by “measure” in the interactive dashboard — shows that the greatest growth occurred for jobs requiring adaptability/flexibility and stress tolerance. Meanwhile, skills such as innovation showed no signs of potent demand.


Soft Skill Importance Varies by Sector

In the aggregate, the 16 soft skills (i.e., work styles) yield an average importance score of 3.9 out of 5 in both Michigan and the nation. Irrespective of geography or occupation, dependability is widely regarded as the most important soft skill for a majority of jobs. Importance scores can vary substantially when looking across occupational groups. 

Try selecting different occupations and geographies to see how importance scores can vary. Hover over any bubble in the chart for more information. Then see the summary at the end of this section for some key findings we discovered.

As shown below, occupations in Community and Social Services generally place the greatest importance on soft skills — with an aggregated importance score of 4.3 out of 5 — while Agriculture and Transportation jobs place the least importance on workers possessing these 16 characteristics, with average importance scores of just 3.25 and 3.58, respectively.

Depending on the nature of work performed in a specific occupational group, a skill that was critical in one sector could become entirely irrelevant in another, or vice versa. For example, innovation is the least important skill in the aggregate, with an average importance score of just 3.4, but its importance becomes greater than average when looking at Arts, Computer, or Education occupations. Compare the examples below for Education, Health Care and Computer occupations.

 

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