Riggers

Select gear such as cables, pulleys, and winches, according to load weights and sizes, facilities, and work schedules.

AI: Fully automatable - Selecting cables, pulleys, and winches is a rules‑based engineering task that AI and software can fully perform given load specs, constraints, and standards by 2025.

Signal or verbally direct workers engaged in hoisting and moving loads to ensure safety of workers and materials.

AI: Partial - AI can provide standardized signals, audio prompts, or augmented guidance and automate some crane functions, but replacing human signalers for complex, situational hoisting safety decisions is not fully reliable by 2025.

Test rigging to ensure safety and reliability.

AI: Partial - AI and sensors can automate inspections and run controlled load tests, yet comprehensive rigging safety testing in diverse field conditions still requires human judgment and intervention, so capability is partial.

Attach loads to rigging to provide support or prepare them for moving, using hand and power tools.

AI: Partial - Robotic manipulators can attach loads in constrained, structured environments, but reliably performing diverse, on‑site load‑attachment tasks with hand and power tools across variable conditions is only partially automatable by 2025.

Control movement of heavy equipment through narrow openings or confined spaces, using chainfalls, gin poles, gallows frames, and other equipment.

AI: Partial - Controlling movement of heavy equipment in confined spaces requires real‑time judgement, tactile feedback, and ad hoc decisions that AI and automation can assist with (teleoperation, sensors) but not fully replace as of 2025.

Tilt, dip, and turn suspended loads to maneuver over, under, or around obstacles, using multi-point suspension techniques.

AI: Partial - Multi‑point suspension and delicate tilting are partly automatable with coordinated crane controls and planning software, but complex, dynamic lifts still require experienced human oversight and intervention.

Install ground rigging for yarding lines, attaching chokers to logs and to the lines.

AI: Partial - Installing ground rigging and attaching chokers in forestry settings is hazardous and unstructured, and while some mechanization exists, full AI automation is not yet practical.

Align, level, and anchor machinery.

AI: Partial - Alignment, leveling, and anchoring benefit from laser tools and automated torque/positioning aids, yet final adjustments and judgment in varied sites remain human tasks.

Fabricate, set up, and repair rigging, supporting structures, hoists, and pulling gear, using hand and power tools.

AI: Partial - Fabrication and repair of rigging and supporting structures can be assisted by robotic welding and tooling, but on‑site variability and troubleshooting prevent full automation today.

Manipulate rigging lines, hoists, and pulling gear to move or support materials such as heavy equipment, ships, or theatrical sets.

AI: Partial - Manipulating rigging lines and hoists can be augmented by powered winches and remote controls, but complex lifts and unstructured environments still require human control.

Clean and dress machine surfaces and component parts.

AI: Partial - Cleaning and dressing machine surfaces can be automated in controlled production contexts (robots, CNC deburring), but many maintenance contexts still need human judgment and dexterity.

Attach pulleys and blocks to fixed overhead structures such as beams, ceilings, and gin pole booms, using bolts and clamps.

AI: Partial - Attaching pulleys and blocks to overhead structures can be partially automated with specialized fastening robots and remote tools, but varied overhead conditions and safety concerns limit full automation.

Dismantle and store rigging equipment after use.

AI: Partial - Dismantling and storing rigging is repetitive and partly automatable through mechanized aids and workflows, but the variability of sites and equipment keeps humans involved.