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needsahuman.

Will AI replace riggers?

Nah.

Most of the work is hands-on load handling, gear inspection and signaling, which software can plan for but not perform. This job scores 84 out of 100 on (higher is safer). Today people do 8% of the work with AI’s help, and 92% still needs a person.

Updated 3 October 2026 49-9096 8151 2026-Q4
Installation, Maintenance, and RepairRiggers49-9096 · 2026-Q4
0% AI does it8% AI helps92% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 92%AI helps 8%AI does it 0%

AI does it: AI can do the task largely by itself. AI helps: a person still does it, faster with AI. Needs a human: AI can do little of it yet.

Why the lift still waits for a person

Rigging is decided at the hook. A rigger sizes up a load, picks cables, slings, shackles and blocks, works out where the center of gravity sits, and attaches the gear so nothing shifts in the air. That judgment happens on a site that changes hour by hour: mud, wind, tight clearances, a load that is heavier on one end than the drawing says.

Software can help with the math. It can lay out a lift plan, check a sling angle, and flag a capacity problem before anyone climbs. What it cannot do is feel a frayed wire rope, reject a damaged shackle, or stand where the crane operator can see the hand signal. Those steps are physical, they are regulated, and someone has to sign for them.

So the honest story for riggers is task erosion rather than a job disappearing. Planning and paperwork move toward software first. Hooking steel, testing the rig and controlling the movement of heavy equipment stay with trained people. The robotics tier this work would need is a dexterous humanoid, which is the hardest class of machine to build and the slowest to arrive on a job site.

What software handles, what it assists, and what stays manual

The slice AI can handle on its own today is small: 0% of task time. The task split above marks which steps sit there, and they are the desk-side parts of the trade, not the parts done in a harness. That share feeds the coverage score, 7 out of 100, which you can read about on the Can AI Do It page.

A second slice is assisted work: 8% of task time. Here a tool speeds a rigger up without taking the task over. Load calculators, digital lift plans and sensor data on crane load cells all shorten the planning stage. A person still checks the output and owns the call.

The rest, 92% of task time, needs a person on the ground. That is where inspecting rigging gear, attaching and securing loads, signaling operators and dismantling the rig after the pick all live. It is also why the headline figure for this job is 84 out of 100 (higher is safer).

What has actually been tested

Not much, in this trade specifically. The parity grade here is D, which means no study has yet put an automated system against certified riggers on the same real lifts and scored the results. There are lift-planning tools and there is crane automation in fixed industrial settings, but neither has been measured head to head against a rigging crew in published work.

What would settle it: an audited field trial on mixed, unfamiliar loads, comparing machine-planned and machine-executed rigging against a certified crew, scored by independent inspectors on setup time, load control and defects found during gear checks. Until something like that exists, no parity number belongs on this page. How the grades work is set out in Is It Better Than A Person?.

When the picture could shift

Most likely after 2045 (8 in 10 of our scenarios). The method behind that window is explained on the replacement-year page.

Two things could pull it earlier. Repetitive industrial lifts inside plants and ports are the easiest to automate, because the loads, the paths and the rigging points repeat. And smart hardware is improving: load cells, sensorized hooks and automated hoists can take over parts of a controlled pick.

Two things hold it back. The work is overwhelmingly physical, and the machine class it would need is a dexterous humanoid, not an arm bolted to a floor. Liability and certification also slow adoption: a rigging failure kills people, so sites keep a qualified, accountable person on the hook. For the wider picture on machines doing physical trades, see the guide on humanoid robots and physical jobs.

How riggers stay needed

Lean into the parts that carry responsibility. First, gear inspection: knowing when a sling, shackle or wire rope comes out of service, and being willing to stop a lift. Second, judging unfamiliar loads, where the weight, balance and pick points are not on any drawing. Third, running the communication on site, from the signal to the crane operator to the brief with the crew.

Two skills pay off. Get fluent with digital lift-planning and load-calculation software, so you check its work instead of waiting for someone else to. And get comfortable with documentation and inspection records kept in apps, since that is where assisted work is moving fastest.

What to do: Put your rigging certifications and your lift-planning software experience on the same page of your resume, so the planning side counts as yours.

Close trades are worth comparing. Look at commercial divers, who rig underwater, and the two cab-side jobs riggers work with daily: crane and tower operators and hoist and winch operators. You can put any two of them side by side on the compare tool.

For context on the trade group, see the other installation, maintenance and repair occupations family and the construction sector page. The pay and employment figures shown above come from BLS. How every score on this page is built is written up in the methodology, and jobs with a similar profile are collected in the safest jobs from AI list.

Frequently asked questions

Will AI replace 3D riggers?

That is a different job. This page covers industrial riggers who move and secure heavy loads on sites, in plants and on ships. A 3D rigger builds skeletons and controls for animated characters, and auto-rigging software has taken over more of that work. If you came looking for the animation role, search the rankings for the art and animation occupations instead.

Will robots replace riggers on construction sites?

Robots already handle repetitive lifts in controlled settings like warehouses and assembly lines. Open construction sites are harder: uneven ground, weather, one-off loads and crews moving around the pick. The robotics section above shows how much of this job is physical and which machine class would be needed. That class is still expensive and rare in the field.

Does AI do lift planning and load calculations?

Software handles a growing share of it. Digital lift planners model crane positions, sling angles and capacity charts, and flag problems before the crew mobilizes. A qualified person still reviews the plan, confirms the real load and signs for it. That is why planning shows up as assisted work in the task split rather than as fully automated work.

Is rigging a good career to start now?

Employment is projected to grow about 4% between 2025 and 2035 (BLS), which is steady rather than fast. Demand follows construction, shipping, energy and entertainment work. Certification matters more than anything else for hiring, and the inspection and signaling duties that make the job hard to automate are the same ones that get you promoted.

What should a rigger learn to stay ahead of automation?

Keep your rigging and signalperson certifications current, then add the digital side: lift-planning software, load monitoring data and inspection apps. Supervisory skills help too, since someone has to own the plan and brief the crew. The needs-a-human tasks listed above are a useful checklist of where to build depth.

Each ridge is a slice of the job's task time.Needs a human 92%AI helps 8%AI does it 0%
The job’s mark

No two jobs leave the same print

Every job gets its own fingerprint, drawn from its code. The amber ridges are the share of task time that still needs a person. Below them, the same ridges are written out in ones and zeros: slate for the work AI helps with, white for the work AI can do.

Riggers, O*NET-SOC 49-9096. 92% of the job’s task time still needs a human, so 92 of every 100 ridges are amber; slate is what AI helps with, white what AI can do.

What AI can and cannot do

The tasks that make up the job, from , and where AI stands on each today: , (a person does it, with AI speeding it up) or . 92% of the still needs a human.

Each block is one task; its height is its share of working time.Needs a human 92%AI helps 8%AI does it 0%
The job's task list: the parts AI can do are blacked out.Needs a human 92%AI helps 8%AI does it 0%
Test rigging to ensure safety and reliability.Needs a human
Signal or verbally direct workers engaged in hoisting and moving loads to ensure safety of workers and materials.Needs a human
Control movement of heavy equipment through narrow openings or confined spaces, using chainfalls, gin poles, gallows frames, and other equipment.Needs a human
Tilt, dip, and turn suspended loads to maneuver over, under, or around obstacles, using multi-point suspension techniques.Needs a human
Select gear, such as cables, pulleys, and winches, according to load weights and sizes, facilities, and work schedules.AI helps
Dismantle and store rigging equipment after use.Needs a human
Attach loads to rigging to provide support or prepare them for moving, using hand and power tools.Needs a human
Manipulate rigging lines, hoists, and pulling gear to move or support materials, such as heavy equipment, ships, or theatrical sets.Needs a human
Align, level, and anchor machinery.Needs a human
Load machines onto trucks to prepare for transportation.Needs a human
Attach pulleys and blocks to fixed overhead structures, such as beams, ceilings, and gin pole booms, using bolts and clamps.Needs a human
Fabricate, set up, and repair rigging, supporting structures, hoists, and pulling gear, using hand and power tools.Needs a human
Clean and dress machine surfaces and component parts.Needs a human
Install ground rigging for yarding lines, attaching chokers to logs and to the lines.Needs a human

Is it better than a person? The evidence

No direct test against people in this job yet. Every study is , and vendor studies are labelled as such.

When could it be replaced?

When AI could largely do this job: no sooner than 2045

Most likely after 2045 (8 in 10 of our scenarios). A range from our of how fast AI improves, how fast employers take it up and what holds it back, not a forecast that the job ends. “” has a strict meaning here. Today’s answer is at the top of the page; this is how it could change.

The sand is the human working years left, measured in the same 40-year glass for every job, so a safe trade starts nearly full and an exposed job with a thin layer.

The sand is the human working years left, in the same 40-year glass for every job.Years still needing a humanYears run out

How this job could shift, year by year

Where the job could sit on our scale each year to 2060, across the ten behind its .

Today
Will AI replace this job?
Nah.
By 2045
20%
of our scenarios have AI largely doing this job by 2045 (Largely.)
10% still have it mostly needing a person (A little. or Nah.)
By 2060
90%
of our scenarios have AI largely doing this job by 2060 (Largely.)
10% still have it mostly needing a person (A little. or Nah.)

We run this job as ten scenarios spread across its replacement range. In each, the score moves towards the bottom band (Largely: AI could largely do the job) by the year that scenario reaches it, slowly at first and faster later, as adoption usually goes. Each bar splits the ten by the band they put the job in. The model stops at 2060. How the timeline works

Share of this job's scenarios in each verdict band, today to 20600%25%50%75%100%2026: 100.0% of scenarios: this job mostly needs a person (Nah.)100%Today2030: 70.0% of scenarios: this job mostly needs a person (Nah.)70%2030: 30.0% of scenarios: AI could do a little of this job (A little.)30%20302035: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2035: 70.0% of scenarios: AI could do a little of this job (A little.)70%2035: 20.0% of scenarios: AI could partly do this job (Partly.)20%20352040: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2040: 20.0% of scenarios: AI could do a little of this job (A little.)20%2040: 40.0% of scenarios: AI could partly do this job (Partly.)40%2040: 30.0% of scenarios: AI could mostly do this job (Mostly.)30%20402045: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2045: 30.0% of scenarios: AI could partly do this job (Partly.)30%2045: 40.0% of scenarios: AI could mostly do this job (Mostly.)40%2045: 20.0% of scenarios: AI could largely do this job (Largely.)20%20452050: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2050: 50.0% of scenarios: AI could mostly do this job (Mostly.)50%2050: 40.0% of scenarios: AI could largely do this job (Largely.)40%20502055: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2055: 20.0% of scenarios: AI could mostly do this job (Mostly.)20%2055: 70.0% of scenarios: AI could largely do this job (Largely.)70%20552060: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2060: 90.0% of scenarios: AI could largely do this job (Largely.)90%2060
Will AI replace the job?Largely.Mostly.Partly.A little.Nah.
Share of this job's scenarios in each band, year by year. Updated with every release.
Show the data
YearLargelyMostlyPartlyA littleNah
Today (2026)0.0%0.0%0.0%0.0%100.0%
20300.0%0.0%0.0%30.0%70.0%
20350.0%0.0%20.0%70.0%10.0%
20400.0%30.0%40.0%20.0%10.0%
204520.0%40.0%30.0%0.0%10.0%
205040.0%50.0%0.0%0.0%10.0%
205570.0%20.0%0.0%0.0%10.0%
206090.0%0.0%0.0%0.0%10.0%

What’s stopping AI taking over?

The things that keep this work with people, strongest first. Each is scored 0 to 100 from work context, licensing and the evidence we have.

LiabilityMistakes are rated 3.9 out of 5 for consequence and decisions 4.1 out of 5 for impact; someone has to answer for them.
Evidence gapNo study yet compares AI with people doing this job, so employers have no proof it is good enough.
Clients want a personFace-to-face contact is rated 4.8 and physical closeness 3.9 out of 5; caring for or serving people is 2.8 out of 5 in importance.
Physical work83% of the task time is physical; robots have been shown on 73% of that time.
RegulationWorkers rate responsibility for others' health and safety 4.5 out of 5.
LicensingUsual entry requirement (BLS): high school diploma or equivalent, then moderate-term on-the-job training.

What would it cost to hand the work to AI?

The share of the year AI could handle (154 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$20–$1,540
A person’s wage for the same hours
$3,010–$7,240

AI cost covers model usage only: no integration, licences, oversight or the human time still needed to review the work. Human cost is the wage for the same hours, without benefits or overheads. As of 2026-10.

Robots and humanoids

AI software can only take the work at a screen. The rest needs a robot that can do it.

83%
of the task time is physical work
Dexterous humanoid
the kind of robot the physical work would need
Not commercial: no cited robot does most of this work; humanoids are at demonstration and pilot stage.

Source: Anthropic Economic Index, 'What work can robots do?' (30 September 2026); O*NET 31.0 task weights.

Which AI skills does this job lean on?

The job’s task time split by what an AI model would need to be good at, and where models stand today.

Each star is a task, grouped by the AI skill it leans on.Needs a human 92%AI helps 8%AI does it 0%
Writing · 0% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 7.9% of time
Strong
Reliable on structured data and rules; uneven on judgement calls with thin information.
Coding · 0% of time
Strong
Agents complete many routine software tasks end to end; larger systems still need people.
Vision and design · 0% of time
Good
Reads documents, images and layouts well; specialist imaging needs dedicated, approved tools.
Speech · 0% of time
Good
Voice agents handle routine calls and live interpreting; complex or sensitive calls still go to people.
Planning and agents · 0% of time
Emerging
Multi-step agents work in narrow, well-tooled workflows; open-ended coordination is unreliable.
Physical manipulation · 92.1% of time
Early
Robots handle structured, repetitive handling; general dexterity outside fixed settings is not commercial.
Care and persuasion · 0% of time
Limited
Can script, coach and advise; trust, presence and accountability still need a person.
Amber matter holds its orbit, slate circles the inner disc, white falls in.Needs a human 92%AI helps 8%AI does it 0%
How exposed is it?

Still needs a human: 84/100↑ safer

The amber matter on the outside holds its orbit: that is the task time that still needs a person. The slate matter circling the inner disc is the work AI helps with. The white matter is the share AI can do; it spirals in and is gone over the edge.

The matter follows the job’s task split: 92% needs a human, 8% AI helps, 0% AI does it. Still needs a human: 84/100 ↑ safer. Will AI replace them? Nah.

What the AIs say

We asked four AI assistants the same question: will AI replace this job in the next 10 years? One word (Yes, Partly or No), then one sentence. Our own answer, from the data: Still needs a human: 84/100 ↑ safer. Will AI replace them? Nah.

ChatGPTPartly

AI will automate some rigging tasks and speed up workflows, but skilled riggers will still be needed for creative problem-solving, customization, and production oversight.

gpt-5.5-2026-04-23 · asked 2026-10-03
ClaudePartly

AI will automate many repetitive rigging tasks (auto-rigging, weight painting, IK/FK setup) but complex character work and creative problem-solving will likely still need skilled riggers to oversee and refine the results.

claude-sonnet-5 · asked 2026-10-03
GeminiNo

Rigging requires complex physical dexterity, real-time spatial judgment, and adaptability to unpredictable, high-risk physical environments that current and near-future robotics cannot fully replicate.

gemini-3.8-flash · asked 2026-10-03
PerplexityPartly

AI will automate some repetitive rigging tasks and reduce certain roles, but skilled riggers will likely remain essential for complex work, judgment, and troubleshooting over the next decade.

sonar · asked 2026-10-03

Assistants answer from what they learned in training (Perplexity also searches the web), so they can be confidently wrong, and the same question can get a different answer tomorrow. Our score is built from task data and graded evidence. Answers collected through DataForSEO.

Cite this page

NeedsAHuman.com (2026). Will AI replace Riggers? Nah. Still needs a human: 84/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/riggers/ (accessed 4 October 2026).

Scores change with each , so cite the release. The data is open under : credit NeedsAHuman.com with a link. Open data · Press

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The badge updates itself with each release and links back to this page.

Sources

  • Tasks and work context: 31.0, ().
  • Jobs, pay and projections: US , and 2025–35.
  • How AI is used today: ; Microsoft Research, .
  • What AI can do: our task ratings ( r1) and the quality evidence register.
  • UK names and employment: coding index and .

How each score is built: methodology. Every figure on this page: open data. Release 2026-Q4.