Robotics Technicians

Maintain service records of robotic equipment or automated production systems.

AI: Fully automatable - AI systems can ingest telemetry, service logs and maintenance inputs to automatically generate, maintain, and update service records reliably.

Modify computer-controlled robot movements.

AI: Fully automatable - AI can create, simulate, optimize, and deploy modified robot motion programs and adjust trajectories using sensor feedback and verification tools.

Evaluate the efficiency and reliability of industrial robotic systems, reprogramming or calibrating to achieve maximum quantity and quality.

AI: Fully automatable - AI can analyze efficiency and reliability metrics, perform diagnostics, and in many cases automatically recalibrate or reprogram systems to optimize throughput and quality, with human oversight for complex cases.

Test performance of robotic assemblies, using instruments such as oscilloscopes, electronic voltmeters, or bridges.

AI: Fully automatable - Programmable test equipment controlled by AI can run performance tests, collect oscilloscope/voltmeter/bridge data, and interpret results to identify faults automatically.

Document robotics test procedures and results.

AI: Fully automatable - AI systems can ingest test logs, sensor data, and templates to automatically generate standardized test procedures and results reports with minimal human editing.

Maintain inventories of robotic production supplies, such as sensors or cables.

AI: Fully automatable - Inventory tracking, demand forecasting, and automated reordering for supplies like sensors and cables are routine tasks that software and AI can fully manage with high reliability.

Develop three-dimensional simulations of automation systems.

AI: Fully automatable - AI tools can automatically generate and run three‑dimensional simulations of automation systems from CAD/models and parameters, producing usable virtual tests and visualizations without continuous human intervention.

Make repairs to robots or peripheral equipment, such as replacement of defective circuit boards, sensors, controllers, encoders, or servomotors.

AI: Partial - Physical repairs such as board replacements, sensor swaps, and motor changes require manual dexterity, fine manipulation, and situational judgment, so automation is partial in 2025.

Troubleshoot robotic systems, using knowledge of microprocessors, programmable controllers, electronics, circuit analysis, mechanics, sensor or feedback systems, hydraulics, or pneumatics.

AI: Partial - AI‑assisted diagnostics improve fault isolation, but complex multi‑domain troubleshooting across electronics, mechanics, hydraulics, and pneumatics still depends on human expert judgment in 2025.

Install, program, or repair programmable controllers, robot controllers, end-of-arm tools, or conveyors.

AI: Partial - AI can generate configurations, program controllers, and provide diagnostics or guided instructions, but physical installation and complex repairs still require on‑site human dexterity and judgement.

Perform preventive or corrective maintenance on robotic systems or components.

AI: Partial - AI can perform predictive maintenance, diagnose faults, and guide or schedule interventions, but many preventive and corrective hands‑on tasks still require human technicians.

Align, fit, or assemble components, using hand tools, power tools, fixtures, templates, or microscopes.

AI: Partial - Vision‑guided robots and automated fixtures can handle many repetitive alignment and assembly tasks, but varied, delicate, or ad‑hoc fittings using hand tools and microscopes often need human skill.

Attach wires between controllers.

AI: Partial - Automated harness machines and robotic manipulators can do standardized wire‑attaching, but variable wiring between controllers and fine manual routing remain largely manual.

Program complex robotic systems, such as vision systems.

AI: Partial - AI can generate and prototype complex robot and vision system code and tune models, but reliable deployment and integration of sophisticated vision systems still need human expertise and validation.

Develop robotic path motions to maximize efficiency, safety, and quality.

AI: Partial - Automated path planning and optimization tools can produce efficient trajectories, yet ensuring safety, edge‑case handling, and final validation for real hardware commonly requires human oversight and tuning.

Train customers or other personnel to install, use, or maintain robots.

AI: Partial - AI can produce interactive tutorials, simulations, AR guidance, and conversational tutoring to teach installation and maintenance, but some hands‑on instructor‑led training and real‑world mentoring remain important.

Build or assemble robotic devices or systems.

AI: Partial - Automated assembly lines can build standardized robotic devices, but custom, complex, or one‑off robotic system builds still require substantial human assembly, integration, and testing.

Fabricate housings, jigs, fittings, or fixtures, using metalworking machines.

AI: Partial - AI can generate CAM programs and machining plans for metalworking machines, but setup, fixturing, tool changes, and quality assurance in fabrication workflows remain partially manual.

Assist engineers in the design, configuration, or application of robotic systems.

AI: Partial - AI can provide design suggestions, configuration options, simulations, and documentation to assist engineers but cannot fully replace expert judgment and integration decisions in complex or safety‑critical designs.

Install new robotic systems in stationary positions or on tracks.

AI: Partial - Planning, instructions, and some robotic-assisted installation steps can be automated, but physical installation in varied environments typically requires human technicians for handling, alignment, and safety.

Train robots, using artificial intelligence software or interactive training techniques, to perform simple or complex tasks, such as designing and carrying out a series of iterative tests of chemical samples.

AI: Partial - AI and simulation-based training methods can train robots for many tasks, including iterative experimental routines, but physical-world complexity and safety constraints limit fully autonomous training for all complex tasks.

Inspect installation sites.

AI: Partial - AI can analyze site photos, plans, and sensor data to perform much of an inspection remotely, but on-site assessments often require humans for access, nuanced judgments, and remediation decisions.

Operate robots to perform customized tasks, such as environmental cleanup or explosive detection operations.

AI: Partial - AI can autonomously control robots for structured tasks and assist operators, but unpredictable environments and safety-critical decisions in cleanup or explosive detection still require human oversight.