Share and intensity of work current AI systems can materially affect.
SOC 17-2199
Robotics Engineers AI displacement risk
The engineers designing robotic and automated systems benefit directly from the automation wave. Simulation, control design, and embedded code are AI-accelerated, while system integration, safety design, and physical testing keep the work deeply hands-on.
Likely potential for exposed tasks to move to software after workflow integration.
This occupation maps to a residual engineering SOC, with mechatronics as its closest task family. Demand is driven by the same automation adoption that pressures other occupations — a structurally protected position.
Distribution
Where Robotics Engineers sits across 620 tracked roles
Displacement pressure 26 — higher than 37% 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 17-2199. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $122,930 (May 2025, US national). The latest BLS row matched SOC 17-2199.
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 Engineers
SOC 17-2199 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 26/100 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 Engineers
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
SOC17-2199
- Core task / ID 20854
Identify and recommend energy savings strategies to achieve more energy-efficient operation.
- Core task / ID 20859
Collect data for energy conservation analyses, using jobsite observation, field inspections, or sub-metering.
- Core task / ID 18156
Monitor and analyze energy consumption.
- Core task / ID 20861
Prepare energy-related project reports or related documentation.
- Core task / ID 20856
Monitor energy related design or construction issues, such as energy engineering, energy management, or sustainable design.
- Core task / ID 20855
Conduct energy audits to evaluate energy use and to identify conservation and cost reduction measures.
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
Design automation and control systems
Exposure 52, automation 26%, augmentation 72%.
O*NET evidence: Design engineering systems for the automation of industrial tasks. (ID 16474)
Create embedded software designs
Exposure 62, automation 32%, augmentation 74%.
O*NET evidence: Analyze, interpret, or create graphical representations of energy data, using engineeri... (ID 18159)
Test and calibrate automated systems
Exposure 38, automation 16%, augmentation 56%.
Research sensors and control devices
Exposure 42, automation 18%, augmentation 62%.
O*NET evidence: Research, select, or apply sensors, communication technologies, or control devices for ... (ID 16471)
TaskExposureAutomationAugmentation
Design automation and control systems5226%72%
Create embedded software designs6232%74%
Test and calibrate automated systems3816%56%
Research sensors and control devices4218%62%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
LowRobotics Software Engineer
Training horizon: 4-9 months. Skill overlap 72. Wage preservation signal 112.
- Learn robot operating frameworks
- Build perception pipelines
- Own simulation test suites
adjacent role
LowAutomation Systems Integrator
Training horizon: 3-8 months. Skill overlap 68. Wage preservation signal 104.
- Commission robotic cells
- Integrate vision systems
- Document safety validations
Comparison guides
Compare the next move before you commit
4-9 months
Robotics Engineers to Robotics Software Engineer
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Robotics Engineers into Robotics Software Engineer.
3-8 months
Robotics Engineers to Automation Systems Integrator
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Robotics Engineers into Automation Systems Integrator.
What the AI risk score means for Robotics Engineers
The displacement pressure score for Robotics Engineers is 26. 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. Create embedded software designs carries 32% automation pressure, while Create embedded software designs carries 74% 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: $122,930 (May 2025, US national). Employment context: Small, fast-growing role designing automation itself. Typical education: Bachelor's degree common; advanced degrees common.
Wage vulnerability is 18, while transition feasibility is 74. 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
- Automation adoption drives demand
- Physical integration resists 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 Engineers, 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.
Mechatronics design
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.
Controls engineering
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.
Embedded systems
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.
AI-assisted simulation
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 Software Engineer, such as learn robot operating frameworks.
- By 90 days, compare internal openings and external postings for Robotics Software Engineer or Automation Systems Integrator and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Robotics Engineers
Will AI replace Robotics Engineers?
The engineers designing robotic and automated systems benefit directly from the automation wave. Simulation, control design, and embedded code are AI-accelerated, while system integration, safety design, and physical testing keep the work deeply hands-on. 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 Engineers work are most exposed to AI?
Create embedded software designs and Design automation and control systems show the strongest automation pressure in this model. Create embedded software designs and Design automation and control systems are better treated as AI-augmented work.
What should Robotics Engineers learn next?
Start with Mechatronics design, Controls engineering, Embedded systems. The most practical adjacent paths in this model are Robotics Software Engineer and Automation Systems Integrator.
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