Share and intensity of work current AI systems can materially affect.
SOC 17-3024
Robotics Technicians AI displacement risk
Every robot installed in a factory needs someone to install, program, calibrate, and repair it — that is this job. Technicians build, maintain, and troubleshoot the automation displacing other roles, putting them on the winning side of the transition.
Likely potential for exposed tasks to move to software after workflow integration.
Unlike the engineers who design robotic systems, technicians make them work on the floor: wiring, programming controllers, reprogramming paths, and keeping cells running. Robot adoption directly increases demand for this role.
Distribution
Where Robotics Technicians sits across 620 tracked roles
Displacement pressure 28 — higher than 43% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-08. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
30 O*NET task statements matched to SOC 17-3024. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $73,900 (May 2025, US national). The latest BLS row matched SOC 17-3024.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify Robotics Technicians
SOC 17-3024 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 28/100 role score and are not an occupation forecast.
+0.4% group wage
-0.5% cognitive employment since mid-2026; 2.9% cognitive unemployment.
Economy-wide: +1.6% GDP and 3.9% unemployment.
-0.3% group wage
-3.9% cognitive employment since mid-2026; 4.5% cognitive unemployment.
Economy-wide: +8.3% GDP and 4.6% unemployment.
-11.5% group wage
-21.5% cognitive employment since mid-2026; 17.9% cognitive unemployment.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for Robotics Technicians
The current evidence import matched 30 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks30
SOC17-3024
- Core task / ID 10892
Test performance of electromechanical assemblies, using test instruments such as oscilloscopes, electronic voltmeters, or bridges.
- Core task / ID 22014
Install or program computer hardware or machine or instrumentation software in microprocessor-based systems.
- Core task / ID 10893
Read blueprints, schematics, diagrams, or technical orders to determine methods and sequences of assembly.
- Core task / ID 22015
Modify, maintain, or repair electrical, electronic, or mechanical components, equipment, or systems to ensure proper functioning.
- Core task / ID 10896
Inspect parts for surface defects.
- Core task / ID 10894
Install electrical or electronic parts and hardware in housings or assemblies, using soldering equipment and hand tools.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Install and program robotic systems
Exposure 34, automation 16%, augmentation 52%.
O*NET evidence: Install or program computer hardware or machine or instrumentation software in micropro... (ID 22014)
Troubleshoot and repair robots
Exposure 30, automation 12%, augmentation 48%.
O*NET evidence: Make repairs to robots or peripheral equipment, such as replacement of defective circui... (ID 21059)
Test performance of assemblies
Exposure 42, automation 20%, augmentation 58%.
O*NET evidence: Test performance of electromechanical assemblies, using test instruments such as oscill... (ID 10892)
Document tests and service records
Exposure 56, automation 30%, augmentation 58%.
TaskExposureAutomationAugmentation
Install and program robotic systems3416%52%
Troubleshoot and repair robots3012%48%
Test performance of assemblies4220%58%
Document tests and service records5630%58%
Transition pathways
Adjacent moves that preserve existing skills
credentialed transition
LowRobotics Engineer
Training horizon: 12-24 months. Skill overlap 64. Wage preservation signal 148.
- Complete engineering coursework
- Build a robot project portfolio
- Learn simulation tools
role redesign
LowAutomation Lead Technician
Training horizon: 2-5 months. Skill overlap 78. Wage preservation signal 118.
- Own cell uptime metrics
- Train junior technicians
- Lead new line commissioning
Comparison guides
Compare the next move before you commit
12-24 months
Robotics Technicians to Robotics Engineer
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Robotics Technicians into Robotics Engineer.
2-5 months
Robotics Technicians to Automation Lead Technician
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Robotics Technicians into Automation Lead Technician.
What the AI risk score means for Robotics Technicians
The displacement pressure score for Robotics Technicians is 28. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Document tests and service records carries 30% automation pressure, while Test performance of assemblies carries 58% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $73,900 (May 2025, US national). Employment context: Hands-on automation role growing with robot installations. Typical education: Associate degree or technical certificate common.
Wage vulnerability is 44, while transition feasibility is 68. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Low displacement pressure
- Robot installations drive direct demand
- Hands-on skills resist remote automation
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Robotics Technicians, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Robot programming
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Electromechanical troubleshooting
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
PLC controllers
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
System calibration
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to Robotics Engineer, such as complete engineering coursework.
- By 90 days, compare internal openings and external postings for Robotics Engineer or Automation Lead Technician and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Robotics Technicians
Will AI replace Robotics Technicians?
Every robot installed in a factory needs someone to install, program, calibrate, and repair it — that is this job. Technicians build, maintain, and troubleshoot the automation displacing other roles, putting them on the winning side of the transition. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of Robotics Technicians work are most exposed to AI?
Document tests and service records and Test performance of assemblies show the strongest automation pressure in this model. Test performance of assemblies and Document tests and service records are better treated as AI-augmented work.
What should Robotics Technicians learn next?
Start with Robot programming, Electromechanical troubleshooting, PLC controllers. The most practical adjacent paths in this model are Robotics Engineer and Automation Lead Technician.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
International Labour Organization / 20 May 2025Generative AI and Jobs: A Refined Global Index of Occupational ExposureOECD / 11 July 2023OECD Employment Outlook 2023: Artificial Intelligence and the Labour MarketO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics