Relatively few workers lose their job because of automation

After 5 years, approximately 8 percent of employees leave the company as a result of automation, according to research from Utrecht University, Boston University and the Dutch Centraal Planbureau. Employees ultimately find a new job, because automation leads to job growth elsewhere. It is therefore not the case that automation always leads to job destruction.

Automation does indeed affect many workers, yet relatively few workers are adversely affected, according to the report: "Automatic Reaction: What Happens to Workers at Firms that Automate?" From Utrecht University professor Maarten Goos and professor Anna Salomons contributed to the research. Salomons is professor of Employment and Inequality. They are both involved in the Future of Work hub of Utrecht University, where researchers from different disciplines are studying the future of work.

Difference between high and low skilled workers

The Harvard Business Review has as main take away from this report: Automation Affects High-Skill Workers More Often, but Low-Skill Workers More Deeply. "Those who do leave, suffer significant economic costs, largely due to spells of unemployment. This affects both their economic prospects and their overall wellbeing. And though welfare programs like unemployment insurance are often framed as the way to address these costs, our data confirm that they don’t nearly make up for the income that workers lose.

Surprisingly, this burden falls more frequently on highly-educated and highly-paid workers. Contrary to conventional wisdom, they are more likely to leave as a result of automation, although they also seem to find new jobs faster."

The real impact of automation is on income and time spent unemployed. The data show that after a spike, tenured workers cumulatively lose about 3,800 Euros in wage and salary earnings over five years on average (about 9% of one year’s income). 

In "What happens to workers at firms that automate" researchers present the first estimates of the economic costs of automation for employees working in the companies where automation takes place. In their empirical analysis they use microdata about companies and their employees over the period 2000 - 2016. They follow employees for up to four years after their company automates and look at the effects on the likelihood of leaving the company, on their pay and how they compensate for any wage loss.