Riggers

Rigger tasks still rely mostly on skilled humans. AI and robots are helping behind the scenes, but haven’t replaced core rigging work. For example, some companies use virtual-reality (VR) and AI tools to model lifts before the job starts – these tools analyze weight and space, then suggest the right cables or pulleys ^[1].

A few specialized robots can move heavy objects: the KEWAZO “LiftBot” will climb scaffolding to carry materials, and smart cranes can automatically swing and lower loads once a human helper ties them on ^{[1] [1]}. Sensors and small cameras are also being added to hoists and cables so computers can flag fraying ropes or worn parts in real time . Even with these tools, riggers still do the hands-on parts – hooking up slings, leveling machines, and directing each move – because those steps need human judgment. (Official job data lists tasks like signaling crane operators and testing gear for safety ^{[2] [2]}, and we found no AI systems fully automating those tasks yet.)

AI and robotics can help tackle big safety and labor challenges in rigging, but high costs and complexity slow adoption. Interest is growing because construction needs lots of workers and safety is a huge concern. One robotics firm notes the U.S. will need ~439,000 new construction workers by 2025 ^[3], and construction has the most workplace deaths (over 1,000 in 2023) ^[3].

Early users of lifting robots and smart cranes report better productivity and safer sites ^[1]. However, a full AI lifting system is expensive (for example, one new 20-foot robotic crane prototype costs on the order of $1 million ^[3]). By contrast, a rigging worker earns about $58,700/year on average ^[4].

Smaller companies especially may not afford big machines. In practice, companies often adopt new lift tools only on large projects or high-risk jobs, while most riggers still work conventionally.