Automation is transforming industries and reshaping the labor market, with significant consequences for millions of workers. While technological advances have always influenced the types of jobs available, the current wave of automation is rapidly accelerating and has the potential to deepen existing inequalities. These shifts raise critical questions about job security, economic mobility, and the role of policy in mitigating workforce disruptions.

A recent LPPI report examines the impact of automation on California’s workforce, highlighting the occupations and demographics most at risk. The findings reveal stark disparities, particularly for Latino workers, who are overrepresented in jobs vulnerable to automation. The report also offers policy recommendations to support workers facing job transitions or displacement.

To better understand the implications, we spoke with the report’s co-authors, Jie Zong and Misael Galdámez, about their research and what automation means for California’s workforce and economic future.

What is automation and why does it matter for workers?

Automation is a process in which technology is used to perform repetitive tasks without human intervention. It has occurred at other points in history and has always reshaped labor markets. In the 20th Century, the increased use of robots in automobile assembly lines displaced many welders and spraypainters, while some workers transitioned to supervisory roles. More recently, fast-casual restaurant chain Sweetgreen announced it would automate all of its locations by 2029, a move which will place robots in kitchens and reduce workers by half.

Understanding the workers whose jobs are most replaceable by technology is important because it helps us understand how we can support workers during transitions. The loss—or even transformation—of a job can alter workers’ abilities to provide for their households and diminish their sense of community and well-being. On the other hand, strong social protections can reduce automation’s negative effects on workers’ economic standings.

It is important to note that when we talk about automation, we refer to “routine” automation—like using self-checkout machines in grocery stores in place of cashiers. We do not consider recent technological advances like Generative AI, as they are still in early development, and the impacts on working-class workers have not been widely observed (yet).

What are the most important highlights from your recent analysis of California workers in jobs at high risk of automation?

Jie: In 2022, 4.5 million California workers were employed in the 20 jobs most vulnerable to automation, including roles like drivers, retail salespeople, cooks, and agricultural laborers. Of these 4.5 million workers, 2.3 million—or over half—were Latino. Importantly, Latinos were the only racial or ethnic group overrepresented in high automation risk jobs relative to their share of state employment.

Many California workers in high-risk jobs face structural barriers, including limited English proficiency, high rates of noncitizenship, and low levels of educational attainment. Latino men are particularly vulnerable, as 44% of Latino men in high-risk jobs have not completed high school. 

What are the most surprising findings from your analysis?

Misael: One surprising finding is the youth of Latino workers in high-risk jobs. About 22% of California Latino workers in high-risk occupations are between ages 16 and 24. Less than half of these young workers are enrolled in school, meaning these jobs are less likely to be temporary arrangements for young Latinos.

How does the overrepresentation of Latino workers in high-risk automation roles intersect with broader trends in labor market stratification?

Misael: Many of the jobs we identify as high-risk are seen as expendable or replaceable societally, perhaps because they usually don’t require a technical or college education. As a result, these jobs pay low wages and have few benefits. For example, the eight largest low-wage occupations in California are also among the 20 largest high automation risk occupations.

These jobs are often filled by workers who lack the resources—like citizenship, education, and language skills—or connections to land a higher-quality job. According to the Latino Data Hub, 80% of California workers without a high school degree are Latino, and low-wage workers are majority Latino. It makes sense, then, that workers in similar jobs with a high risk of being automated are vulnerable Latino workers.

In light of your findings, what specific industries or regions in California should policymakers prioritize for intervention, and why?

Jie: Regional interventions should focus on communities where single industries account for large shares of employment and where few well-paying, high-quality jobs are available. 

For example, In Southern California’s Inland Empire, many high automation risk workers—like truck drivers and freight movers—are employed in the transportation, distribution, and logistics industry. The local logistics sector is expected to automate, and automation in the sector will reshape regional employment and disrupt livelihoods, as the transportation, distribution, and logistics industry employs over one in ten Inland Empire workers. Additionally, over half of jobs in the IE cannot provide workers with a middle-class standard of living, leaving few opportunities for economic stability.

In the Central San Joaquin Valley, 14% of workers are employed in agriculture, a rapidly automating industry. In the past, the adoption of technologies like the mechanical tomato harvester led to significant job losses for farmworkers, and our research identifies agricultural workers as similarly vulnerable today. Further, less than half the jobs in the region allow workers to meet the high cost of living. 

By focusing investment in regions where high-quality job opportunities are few and far between and where automation has far-reaching implications for major industries, policymakers can chart a new course for regional economies.

Read the full report here.