Anticipating the impacts of light-duty vehicle electrification on the U.S. automotive service workforce


 This paper draws on publicly available data from the Current Population Survey and the Bureau of Labor Statistics, as well as estimates from 25 studies, to understand how a transition to electric vehicles may impact workers in the vehicle services sector. We examine the structure of the current vehicle service workforce, characterize its unique vulnerabilities along several dimensions, and evaluate how it may be impacted by rising EV adoption. Careful attention to how the benefits and costs of widespread vehicle electrification are distributed is essential to inform effective policy to support workers and communities through an EV transition, and this analysis provides a starting point for understanding these impacts. More generally, the case of vehicle service workers suggests that understanding indirect, system-wide impacts of the broader clean energy transition may inform a more just transition, which may in turn help to maintain and expand support for necessary climate action.

Addressing climate change will require decarbonization of the United States (U.S.) economy, which will lead to the decline of certain industries and the creation of new ones. With such shifts may come changes in the location, demographics, and skills of workers, and detrimental impacts may disproportionately fall on disadvantaged communities. Ensuring equitable transitions requires anticipating and avoiding such an uneven distribution of benefits and burdens, as well as promoting inclusive decision-making and reconciling past inequities [1]. To date, many have focused on the future of jobs in activities linked to fossil energy, such as coal mining or oil and gas extraction. However, the workforce consequences of energy transition are likely to be much broader.
For example, vehicle electrification may not only displace fossil energy needs and require different skills to manufacture vehicle powertrains, but also put vehicle-related service jobs at risk. We find that these jobs far outnumber direct vehicle manufacturing jobs and these workers have, on average, lower incomes, fewer postsecondary degrees, and lower rates of union membership, which may leave them more exposed in an energy transition. These unequally distributed impacts could fuel opposition to the energy transition that would enable the necessary deep cuts in greenhouse gas (GHG) emissions.

Vehicle after-sales services: workers at risk?
Addressing the roughly one-third of U.S. GHG emissions from transportation is essential to fully decarbonize the U.S. economy [2]. Electrifying light-duty vehicles with clean electricity is expected to play a central role, as the main cost-competitive substitute for using fossil fuels in the internal combustion engine.
Prior studies have focused mainly on automotive manufacturing workforce impacts and less on what happens once the car leaves the factory. Compared to manufacturing, nearly four times as many automotive workers are involved in downstream activities like sales and aftermarket services. Jobs associated with vehicle services alone-including refueling, repair, maintenance, car washes, and part and accessory sales-employ more U.S. workers than the manufacturing and sales components of the automotive industry combined (see figure 1). Changes in refueling practices, maintenance schedules, and repair needs could substantially affect these aftersales service jobs [3][4][5][6]. Beyond aggregate shifts, service worker impacts will also vary across U.S. regions.
Our analysis provides a starting point for understanding impacts on vehicle services workers. We use publicly available data from the Current Population Survey [8] and the Bureau of Labor Statistics [7] as well as existing literature to show what the vehicle service workforce looks like today, how it is uniquely vulnerable, and how it may be impacted by rising electric vehicle (EV) adoption.

Who are vehicle service workers?
In comparison to automotive manufacturing workers, service workers are far more dispersed and most concentrated in some of the least populated states (see figure 2).
Service workers have several characteristics that make them particularly vulnerable to transitions. For example, the average income of a vehicle service worker is 40% lower than the average U.S. worker [8]. Additionally, nearly 60% of vehicle service workers have just a high school diploma or less, compared to 40% in the U.S. workforce at large [8]. About twothirds of all jobs in the U.S. require some level of  The concentration of vehicle after-sales service workers is highest in sparsely populated states, but they are still more evenly distributed than automotive manufacturing workers. Sources: Flood et al [8], U.S. Census [9]. postsecondary education [10], which leaves a relatively small pool of new opportunities for these service workers that may be displaced. Union membership, which can help to protect wages and benefits during transitions, is relatively low among vehicle service workers. Compared to about 12% of the U.S. workforce, less than 1% of vehicle service workers are covered by a union [8].
Effects on the after-sales service labor force will also disproportionately impact certain sociodemographic groups. Nearly two-thirds of vehicle service workers are white men [8]. At the same time, vehicle service workers also have disproportionate representation from certain underrepresented groups. For example, vehicle service workers are nearly twice as likely to be Native American and slightly more likely to be immigrants than the average U.S. worker [8].

How will EVs change vehicle services?
While a transition to EVs is likely to be gradual, it is not clear what the impact will be on the revenues of vehicle service businesses, or on the jobs and nature of work of their employees. EVs do not use gasoline or oil, very rarely need brake services, and do not have as many wearing parts to be replaced as internal combustion engine vehicles (ICEVs), all of which are key sources of conventional aftermarket revenue. On the other hand, EVs still require repairs after collisions and have higher electronic content than ICEVs, the latter of which may require additional skills [3].
To understand these impacts, we assessed 25 studies on the impacts of electrification on the vehicle services sector. For this case study, we focus on the transition for light-duty vehicles. The implications for heavy-duty vehicles would raise a related but distinct set of challenges.
We found that projections of the impacts of electrification on the vehicle service sector vary widely and reflect numerous sources of uncertainty, including frequency of services, labor hours per visit, worker wages, and part costs. In some cases, such as for maintenance and repair, authors differ not only on the magnitude but even the direction of the change. A similar 2021 European Union study on maintenance and repair also presented a set of studies with large variation in estimates, although the authors concluded based on three selected studies that the trend is towards a decrease in demand [11].
Of the 25 studies we assessed, 20 estimated changes in revenue or cost to consumers. Each study defines services differently, making direct comparisons of revenue and cost impacts difficult. For example, three studies define maintenance narrowly as the services listed in a vehicle's service manual [3,12,13], while another study defines maintenance as any costs required to keep a vehicle operational [14]. For details on each study's definitions and assumptions, see the appendix.
Only one study quantified the change in labor demand for gas stations, assuming that it will decrease linearly to zero with increasing EV adoption [4]. This projection may overstate job losses if gas station infrastructure is repurposed for electric vehicle charging and convenience stores remain open, as 90% of gas station employees work at establishments that are also convenience stores [15]. The three studies we found that estimate changes in charging labor demand vary widely in their implicit estimates, from 2 to 40 jobs created per 10,000 new EVs in the fleet [4,16,17].
When it comes to demand for mechanics, findings were more consistent across the multiple studies we reviewed. All but one indicated that combined maintenance and repair revenue will decrease for EVs relative to ICEVs. However, the magnitude of the loss estimated varied widely, from a loss of 8% to nearly 80% per EV. A few studies estimated changes in repair revenue separately from maintenance revenue. The expected changes in repair revenue ranged from about −30% to +20% per EV based on vehicle model. While maintenance revenue changes might closely parallel labor demand changes, the situation may be different for repair if influenced more by the price of parts. Moreover, EVs may even be more likely than ICEVs to lead to total losses after a collision and never make it through the repair shop [18]. The three studies that allow a comparison of impacts on estimated hours spent on repairs versus estimated revenue suggest they are not necessarily proportional.
Additional labor demand changes in vehicle services, such as in spare part and accessory sales, are likely but have not yet been quantified in the literature. For instance, many of the maintenance activities that are being reduced, such as oil changes and brake replacements, are key sources of revenue for automotive part retailers. Sales of products for at-home vehicle repairs may also take a hit as EV adoption grows.
Even if there are enough revenue and labor hours to support the maintenance and repair workforce after the transition to EVs, they will still face challenges to working on EVs. EV electronics are substantially higher voltage than conventional vehicles, which necessitates new equipment and worker training, both of which may be a strain on small businesses. Some experts also claim that mechanics are 'scared' to work on EVs because they are high-voltage and unfamiliar to them, so some shops choose not to work on EVs at all [19,20].

Exploring the geography of impacts
We develop a simplified framework for mapping local changes, starting with the assumption that the number of workers needed per ICEV is a function of the current number of ICEVs and vehicle service workers in each state. Using the percent change in workers needed per vehicle between ICEVs and EVs, we can calculate absolute worker demand for a vehicle fleet with any combination of ICEVs and EVs. As EV adoption increases and the number of ICEVs fall, we can determine how the needs of this future fleet compare to today. We use maintenance and repair to project these changes because we have the most information for these activities, with the assumption that revenue is a proxy for labor demand. To illustrate how the number of maintenance and repair workers in each state could change by 2030, we create a set of scenarios to explore uncertainty in both the change in labor demand for labor per EV and in the number of vehicles electrified. See the appendix for more information on the model and the scenarios.
The projected effect of vehicle electrification on service worker jobs varies significantly based on the assumed change in labor required per EV. In addition, there is also variation between states, with the most pronounced impacts concentrated where services account for a larger share of total employment (e.g. California, Nevada, Utah, and Colorado). The differences between states are relatively subtle in the low EV adoption scenario, but higher adoption rates amplify differences, since states with higher adoption today end up with higher future adoption. This is because we also assume a constant multiplier for adoption scenarios across states. If we instead assume that states with the most EVs today continue to grow the fastest, vehicle service workers in those states would be affected disproportionately.

Weathering the transition
If workers do not see a future in a clean energy transition, climate and clean energy policies are likely to face a rough road ahead. Labor opposition to clean energy transitions has been strong in industries that the transition will directly affect, such as the coal mining industry, which employs only one-fourth as many workers as the automotive repair industry [20,21].
Careful attention to how the benefits and costs of widespread vehicle electrification are distributed is essential for effective policy to support workers and their communities through an EV transition. While further work is needed to reconcile conflicting findings of the studies surveyed above, our results are clear that service workers are a substantial and understudied population that will require attention during a transition. Here, deliberate policy that anticipates workforce challenges can reduce potential frictions in job transitions. For example, state and local gov-ernments and large employers should support career counseling, certificate, and apprenticeship programs to help workers identify skill-adjacent opportunities in clean energy or other growing service occupations. In states that face the most acute effects, governments could also explicitly include vehicle services workers in workforce-focused stakeholder consultations as part of their transition planning efforts. They could also consider engaging unions in that process, and support organized labor to upskill and attract this distributed workforce.
The case of vehicle service workers suggests that understanding indirect, system-wide impacts of a low-carbon transition may inform a more just transition, which may in turn help to maintain and expand support for climate action.

Data availability statement
The data that support the findings of this study are openly available at the following URL/DOI: https:// doi.org/10.18128/D030.V9.0. The normalized change is based on the percent difference in the cost of an ICEV and an EV. Negative values represent a lower cost for EVs than ICEVs. -The normalized change is based on the percent difference in the labor required for an ICEV and an EV. Negative values represent less labor needed for EVs than ICEVs.

Appendix B. Model assumptions
To go beyond the net changes in the national vehicle services workforce, we explore how the impacts of vehicle electrification may affect vehicle service workers in individual states. We develop a simplified framework for mapping local changes, starting with the assumption that the number of workers needed per ICEV (i.e. the labor demand per ICEV) is a function of the current number of ICEVs and vehicle service workers in each state. Using the percent change in labor demand per vehicle between ICEVs and EVs, we can calculate absolute labor demand for a vehicle fleet with any combination of ICEVs and EVs. As EV adoption increases and the number of ICEVs fall, we can determine how the needs of this future fleet compare to today. For demonstration purposes, our model is based on only a single sector within the vehicle use phase: vehicle maintenance and repair. We use maintenance and repair to project these changes because we have the most information for these activities, with the assumption that revenue is a proxy for labor demand.
The model for labor takes the following as inputs (using 2019 as the base year): • Current number of workers per state in sector code '8770 Automotive Repair and Maintenance' (Flood et al [8] • Estimated percent change in maintenance and repair revenue between an ICEV and an EV (from table A1 above). • Current number of residents per state (U.S. Census [9]).
The model is based on the following assumptions: • The number of workers needed per EV varies by state and is a function of the current number of EVs and workers in each state. • The number of total vehicles in each state is constant in all scenarios, implying that for every vehicle sold, a vehicle is retired. • Changes in revenue are a close proxy for changes in labor demand.
Model description: • We start by assuming that the total workers needed for maintenance and repair is a function of the workers needed for each EV and the workers needed for each conventional vehicle, which are W EV and W CV , respectively. We multiply the workers needed per vehicle by the number of each type of vehicle to get the total number of workers needed: • If we change the value for EV adoption, A, the relative number of EVs and CVs changes and so does W total : • With data for the number of repair and maintenance workers in each state as well as the number of conventional and electric vehicles, we solve for W EV and W CV . To do that, we introduce a second equation, which is the percent change in workers needed per vehicle when you transition to an EV. The value for percent change in workers per vehicle, or ∆W, come from table A3 above: • Combining equations (2) and (3), we get equation (4). When we apply this process to each state, for both the initial and final adoption levels, we can calculate the expected change in workers in each state: To illustrate how the number of maintenance and repair workers in each state could change by 2030, we create a set of scenarios to explore uncertainty in both the percent change in demand for labor per electrified vehicle and in the number of vehicles electrified. We constructed the following two sets of scenarios: • Adoption scenarios: To capture uncertainty in the number of electric vehicles adopted, we construct two alternative adoption scenarios for 2030. 'Low Adoption' represents a seven-fold increase in adoption in each state and 'High Adoption' represents a 16-fold increase in adoption. These are based on the IEA 2021 Global EV Outlook adoption scenarios [40]. The IEA 'State Policies Scenario' projects an increase in the portion of EVs in the U.S. fleet from about 1% to 7%, and the 'Sustainable Development Scenario' projects an increase from about 1% to 16%. We assume that these adoption scenarios will be uniform across states (i.e. a constant multiplier), although adoption to date certainly has not been uniform. • Labor change scenarios: To capture uncertainty in the first variable (percent change in labor demand per electrified vehicle), we run our model using the lowest and highest labor change estimates across the literature, in terms of whether they are most or least harmful to workers. The 'Worst Case' represents a decrease in maintenance and repair revenue of 78% per EV. The 'Best Case' represents an increase in maintenance and repair revenue of 26% per EV. These are the lowest and highest values we found from the literature. Since changes in revenue are likely actually a lower bound for changes in labor demand, these if anything underestimate the labor required for EVs. The number of maintenance and repair workers in each state comes from the 2019 Current Population Survey [8].