Automotive body and glass repairers

AI Overlap Index
28.0 / 100
Insulated

Embodied skill, frontline presence, or deep institutional judgment. Most insulated.

SOC · Installation Maintenance And Repair

Bureau of Labor Statistics
Median pay
$50,680/yr
Hourly
$24/hr
Jobs 2024
193,000
Projected 2034
196,500
10-yr outlook
+2% · Slower than average
Employment change
3,500
Entry education
High school diploma or equivalent
SOC code

Signal composition

how the 0-100 score is assembled

Task Automation Impact weight 60%
12.1
contribution to AOI: 7.3
Automation Potential weight 10%
20.0
contribution to AOI: 2.0
Market Pressure weight 15%
55.0
contribution to AOI: 8.2
Entry Barrier Erosion weight 15%
70.0
contribution to AOI: 10.5

By seniority

multiplicative adjustment from category curve

Entry
32.2
mult 1.15x
Mid
28.0
mult 1.00x
Senior
23.8
mult 0.85x

Entry-level roles carry the brunt because they concentrate the most automatable subset of tasks. Senior work is insulated by judgment, relationships, and accountability.

Task-level analysis

scored 0-100 for current-generation AI feasibility, weighted by BLS-stated importance

10 tasks · model: claude-sonnet-4-5-20250929
Supporting t10

Review damage reports and prepare cost estimates

AI can analyze damage reports, cross-reference parts databases, apply labor rate calculations, and generate detailed estimates with minimal human input. Modern systems already automate much of this process, requiring only light review for unusual cases or customer communication.

BLS evidence: Body repairers 'review damage reports, prepare cost estimates, and plan work.'

68
automation
Important t8

Sand, buff, and prime refurbished and repaired surfaces

Involves operating power tools on curved, irregular surfaces requiring constant pressure adjustment and angle changes based on tactile and visual feedback. While more routine than welding, the physical manipulation across variable body panel geometries and the need to avoid over-sanding limits current automation.

BLS evidence: Body repairers 'sand, buff, and prime refurbished and repaired surfaces.'

15
automation
Important t9

Prepare windshield frames and surfaces for installation or repair

Requires cleaning, priming, and preparing surfaces through physical manipulation with various tools and chemicals. Involves assessing surface condition through touch and sight, adapting technique to contamination or rust, and working in confined spaces around vehicle frames.

BLS evidence: Glass repairers 'check windshield frames for rust,' 'clean windshield frames and prepare them for installation,' and 'clean damaged areas and prepare the surfaces for repair.'

13
automation
Core t1

Inspect vehicles for structural and body damage

Requires physical presence to walk around vehicles, assess hidden damage through tactile inspection, and make judgment calls about structural integrity in unpredictable damage patterns that computer vision cannot reliably evaluate without physical probing.

BLS evidence: Body repairers 'inspect cars for structural damage' and glass repairers 'examine damaged glass or windshields and assess repairability.'

12
automation
Important t7

Stabilize windshield chips and cracks with clear resin

Requires precise manual application of resin to specific crack patterns, physical assessment of chip depth and extent, and fine motor control to inject resin properly. While somewhat standardized, the physical manipulation and quality judgment in variable lighting/temperature conditions limits automation.

BLS evidence: Glass installers and repairers 'stabilize chips and cracks with clear resin' using specialized tools such as vacuum pumps.

11
automation
Core t4

Repair minor body damage by hammering out or patching dents

Involves skilled manual manipulation with hammers and dollies, requiring haptic feedback to feel metal response, judgment about when to stop working an area, and adaptation to each unique dent's characteristics in non-standardized vehicle body panels.

BLS evidence: Body repairers 'hammer out or patch dents, dimples, and other minor body damage.'

10
automation
Core t6

Install replacement windshields and window glass

Demands careful handling of large, fragile glass panels, precise fitting into frames that may be slightly misaligned, application of adhesives with proper technique, and physical manipulation in confined spaces. Current robotics lack the dexterity and adaptability for this variable task.

BLS evidence: Glass repairers 'apply urethane sealant to the windshield frames' and 'install replacement glass.'

9
automation
Core t2

Remove damaged body parts and glass components

Demands fine motor skills and physical manipulation in confined, variable spaces around damaged vehicles. Requires handling sharp metal, applying appropriate force, and adapting to unique damage configurations that current robotics cannot handle in typical auto body shop environments.

BLS evidence: Body repairers 'remove damaged body parts, including bumpers, fenders, hoods, grilles, and trim' and glass repairers 'remove glass that cannot be repaired.'

8
automation
Core t5

Fit, attach, and weld replacement parts into place

Requires precise welding in awkward positions on vehicle bodies, fitting parts that may not align perfectly due to prior damage, and making real-time adjustments. The combination of fine motor control, spatial reasoning in 3D, and safety-critical welding is beyond current robotic capabilities in variable repair contexts.

BLS evidence: Body repairers 'fit, attach, and weld replacement parts into place.'

7
automation
Core t3

Realign car frames and chassis to repair structural damage

Requires specialized hydraulic equipment operation, precise force application based on tactile feedback, and real-time adjustment to metal behavior during straightening. The physical manipulation and safety-critical nature in unpredictable damage scenarios is beyond current AI+robotics integration.

BLS evidence: Body repairers 'realign car frames and chassis to repair structural damage' and 'restore the structural integrity of car frames to manufacturer specifications.'

6
automation

Task heatmap

automation score by task, sorted by weighted contribution

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External signals and sources

category-level priors and BLS fields that feed the four non-task signals

Automation Potential
20
karpathy 2/10
  • Karpathy/BLS Digital AI Exposure (0-10 scale rescaled to 0-100)
Market Pressure
55
outlook: Slower than average
  • BLS projected outlook: Slower than average (2%)
  • Indeed demand signal (monthly refresh pending)
Entry Barrier Erosion
70
ed: High school diploma or equivalent
  • BLS typical entry-level education: High school diploma or equivalent
  • Credential trend signal (annual refresh)

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