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Will AI replace plasterers and stucco masons?

Nah.

Nearly all of the work is hands-on mixing, coating and texture finishing on site, where AI can only assist. This job scores 86 out of 100 on (higher is safer). Today people do 7% of the work with AI’s help, and 93% still needs a person.

Updated 3 October 2026 47-2161 5321 2026-Q4
Construction and ExtractionPlasterers and Stucco Masons47-2161 · 2026-Q4
0% AI does it7% AI helps93% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 93%AI helps 7%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 work stays on the trowel

Will AI replace plasterers and stucco masons? The task list above answers that better than any forecast. A plasterer’s day happens in front of a wall. You mix plaster or stucco to a consistency that suits the mix, the weather and the surface, then get it on and worked before it sets. That timing is judgment, and it shifts hour to hour.

Applying coats over lath, masonry or drywall is not one motion repeated. A ceiling, an arch, a window return and a patch beside existing work each need different pressure and a different angle. Matching an existing finish by eye, whether it is a dash, a float or a hand-troweled swirl, is done against a wall that is already there. There is no file to copy.

Then there is everything around the wall. Surfaces get cleaned and prepped, damaged material gets cut back, scaffolding goes up, and the crew works around other trades on a site that changes daily. Median pay runs about $57,660 a year and the trade holds roughly 19,310 US jobs, with employment projected to grow 2.8% through 2035 (BLS, 2025). A small trade doing varied work is a poor target for purpose-built machines.

What AI does, what it assists, what it leaves alone

Share of task time AI could handle on its own today: 0%. The tasks nearest that line are the desk ones: working out how much material a job needs and what it will cost, and keeping job records straight. Software can draft both, though someone still checks the figure before the order goes in.

AI assists on 7% of task time. Layout is the clearest case. Setting guide wires, screeds and grounds can start from a laser scan or a measured model, and a tablet can flag where a surface sits out of plumb before the first coat goes on. Checking a finished surface for flatness is another one a sensor can support. The tool measures; the plasterer corrects. Our coverage method sets out how that task time is counted.

People hold 93% of task time. Spreading and finishing coats, and building decorative or textured finishes by hand, sit there, along with the prep, patching and scaffolding work that surrounds them.

What the evidence actually shows

No study in this job’s evidence list puts a machine against a working plasterer on a real wall. That is why the parity grade reads D. On our scale, a grade of D means the comparison has not been measured, so we publish no parity number for this trade. The parity grading page explains the scale.

The test that would settle it is easy to describe and hard to run: a timed job on an occupied building, with corners, a ceiling and a patch against existing texture, done by a machine crew and by a journeyman crew, then judged on flatness, texture match, cleanup and callbacks. Clips of spray-and-trowel machines running plain new-build walls do not answer that question. Until someone runs the comparison, the honest position is that it has not been measured.

When this could change

Most likely after 2048 (8 in 10 of our scenarios). The replacement-year method explains what that window measures and why it is published as a range.

Two things could pull it earlier. Cheaper mobile robot platforms that can move over a rough floor and reach a ceiling would remove the main hardware barrier on plain, repetitive walls in new construction, a point covered in our guide to humanoid robots and physical jobs. Work could also leave the site altogether if more panels are finished in a factory, where a fixed arm can run flat surfaces all day.

Two things push it later. The trade’s time goes on physical work in unstructured space: ladders, scaffolds, occupied rooms, uneven ground. That is the hardest setting for a machine to work in reliably. The market is also small. With about 19,310 US jobs (BLS, 2025), there is little pull to fund hardware built only for plastering, so this trade waits on general-purpose machines rather than getting its own. Both points sit in the blockers and robotics panels above, and the full scoring method shows how they feed the timing.

How to stay needed in the trade

Lean into the parts the task list leaves with people. Restoration and repair on existing buildings, where damage is cut back and new work is blended into old, is the opposite of a repeatable task. Decorative and ornamental finishes, including run cornice and hand textures, hold their value because the customer is buying the hand. Third is prep and diagnosis: reading why a wall failed before anything goes back on it.

Two skills pay. One is estimating and takeoff with digital tools, since that is where software is strongest and where a plasterer who checks the output stays in charge of the job. The other is running a crew, meaning scheduling, quality control and site coordination, which is also the route into supervision across construction trades work.

What to do: take one restoration or ornamental job this year and photograph the texture matches for your portfolio.

Nearby trades share the same mix of hand finishing and layout: drywall and ceiling tile installers, tapers and cement masons and concrete finishers. Put any two of them side by side on the compare page, look at the wider construction sector, or browse the list of jobs that mostly need a person.

Frequently asked questions

Are plastering robots being used on building sites?

Spraying and screeding machines exist and are used on large, flat, new-build surfaces, and clips of them travel fast online. They work best where the wall is plain, the floor is level and access is clear. Repairs, corners, ceilings and texture matching in occupied buildings are still done by hand. The robotics panel above shows which hardware class this trade would need.

What jobs are hardest for AI to replace?

Work that is physical, varied and done in spaces a machine cannot predict is the hardest: skilled trades on site, hands-on care, emergency response, and anything where a single mistake is expensive to undo. The common thread is not intelligence but hands, access and accountability. The rankings page on this site sorts every US occupation we score, so you can see where trades sit against desk work.

What jobs will be gone by 2030 due to AI?

No credible source can name occupations that end on a fixed date. What the data shows is task erosion inside jobs and fewer openings at the entry level, rather than whole jobs disappearing. In plastering, the estimating and record-keeping side shifts before the wall does. The timing chart above shows the published range for this trade instead of a single date.

Will AI replace construction workers more broadly?

Construction mixes office work that software handles well with site work it barely touches. Design, scheduling, takeoff and progress tracking are changing fastest. Pouring, framing, finishing and repair stay physical. Timing varies a lot by trade, so it is more useful to compare individual jobs than the industry as a whole. The construction sector page groups the trades we score.

Is plastering a good career to start now?

Employment is small but steady: about 19,310 US jobs, median pay around $57,660, and projected growth of 2.8% through 2035 (BLS, 2025). Earnings rise with speed, finish quality and the ability to handle restoration or ornamental work. Entry is usually through an apprenticeship or helper work. The main risks are physical wear and construction cycles rather than software.

What skills keep a plasterer in demand?

Texture matching and restoration, running a small crew, and accurate estimating. Reading a substrate problem correctly before recoating prevents callbacks, and callbacks are what cost money. Digital takeoff and good photo records help you win work and defend it later. The skills and blockers panels above list what this trade relies on, and the section on staying needed suggests where to start.

Each ridge is a slice of the job's task time.Needs a human 93%AI helps 7%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.

Plasterers and Stucco Masons, O*NET-SOC 47-2161. 93% of the job’s task time still needs a human, so 93 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 . 93% of the still needs a human.

Each block is one task; its height is its share of working time.Needs a human 93%AI helps 7%AI does it 0%
The job's task list: the parts AI can do are blacked out.Needs a human 93%AI helps 7%AI does it 0%
Cover surfaces such as windows, doors, or sidewalks to protect from splashing.Needs a human
Apply coats of plaster or stucco to walls, ceilings, or partitions of buildings, using trowels, brushes, or spray guns.Needs a human
Clean and prepare surfaces for applications of plaster, cement, stucco, or similar materials, such as by drywall taping.Needs a human
Create decorative textures in finish coat, using brushes or trowels, sand, pebbles, or stones.Needs a human
Mix mortar and plaster to desired consistency or direct workers who perform mixing.Needs a human
Clean job sites.Needs a human
Rough the undercoat surface with a scratcher so the finish coat will adhere.Needs a human
Set up scaffolds.Needs a human
Cure freshly plastered surfaces.Needs a human
Apply weatherproof, decorative coverings to exterior surfaces of buildings, such as by troweling or spraying on coats of stucco.Needs a human
Determine materials needed to complete the job and place orders accordingly.AI helps
Apply insulation to building exteriors by installing prefabricated insulation systems over existing walls or by covering the outer wall with insulation board, reinforcing mesh, and a base coat.Needs a human
Spray acoustic materials or texture finish over walls or ceilings.Needs a human
Install guide wires on exterior surfaces of buildings to indicate thickness of plaster or stucco and nail wire mesh, lath, or similar materials to the outside surface to hold stucco in place.Needs a human
Mold or install ornamental plaster pieces, panels, or trim.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 2048, most likely after 2060

Most likely after 2048 (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
10%
of our scenarios have AI largely doing this job by 2045 (Largely.)
90% still have it mostly needing a person (A little. or Nah.)
By 2060
10%
of our scenarios have AI largely doing this job by 2060 (Largely.)
90% 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: 100.0% of scenarios: this job mostly needs a person (Nah.)100%20302035: 90.0% of scenarios: this job mostly needs a person (Nah.)90%2035: 10.0% of scenarios: AI could do a little of this job (A little.)10%20352040: 90.0% of scenarios: this job mostly needs a person (Nah.)90%2040: 10.0% of scenarios: AI could mostly do this job (Mostly.)10%20402045: 90.0% of scenarios: this job mostly needs a person (Nah.)90%2045: 10.0% of scenarios: AI could largely do this job (Largely.)10%20452050: 90.0% of scenarios: this job mostly needs a person (Nah.)90%2050: 10.0% of scenarios: AI could largely do this job (Largely.)10%20502055: 90.0% of scenarios: this job mostly needs a person (Nah.)90%2055: 10.0% of scenarios: AI could largely do this job (Largely.)10%20552060: 90.0% of scenarios: this job mostly needs a person (Nah.)90%2060: 10.0% of scenarios: AI could largely do this job (Largely.)10%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%0.0%100.0%
20350.0%0.0%0.0%10.0%90.0%
20400.0%10.0%0.0%0.0%90.0%
204510.0%0.0%0.0%0.0%90.0%
205010.0%0.0%0.0%0.0%90.0%
205510.0%0.0%0.0%0.0%90.0%
206010.0%0.0%0.0%0.0%90.0%

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.

Clients want a personFace-to-face contact is rated 4.7 and physical closeness 3.4 out of 5; caring for or serving people is 3.1 out of 5 in importance.
Evidence gapNo study yet compares AI with people doing this job, so employers have no proof it is good enough.
Physical work93% of the task time is physical; robots have been shown on 82% of that time.
RegulationWorkers rate responsibility for others' health and safety 3.8 out of 5; the sector has its own rules on who may do the work.
LiabilityMistakes are rated 2.8 out of 5 for consequence and decisions 3.4 out of 5 for impact; someone has to answer for them.
LicensingUsual entry requirement (BLS): no formal educational credential, then long-term on-the-job training.

What would it cost to hand the work to AI?

The share of the year AI could handle (96 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$10–$960
A person’s wage for the same hours
$1,820–$4,450

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.

93%
of the task time is physical work
Mobile robots
the kind of robot the physical work would need
Commercial in warehouses, hospitals and some outdoor sites; hands are still limited.

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 93%AI helps 7%AI does it 0%
Writing · 0% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 0% 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 · 6.9% of time
Emerging
Multi-step agents work in narrow, well-tooled workflows; open-ended coordination is unreliable.
Physical manipulation · 93.1% 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 93%AI helps 7%AI does it 0%
How exposed is it?

Still needs a human: 86/100↑ 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: 93% needs a human, 7% AI helps, 0% AI does it. Still needs a human: 86/100 ↑ 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: 86/100 ↑ safer. Will AI replace them? Nah.

ChatGPTPartly

AI and robotics may automate some measuring, planning, and repetitive application tasks, but skilled plasterers will still be needed for complex finishes, repairs, judgment, and on-site problem-solving.

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

Plastering requires physical dexterity, adaptation to irregular surfaces, and on-site problem-solving that current robotics and AI cannot replicate cost-effectively within this timeframe.

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

While specialized construction robots may increasingly handle large, flat commercial surfaces, human craftspeople will remain essential for the intricate, adaptive physical labor required in residential and renovation work.

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

AI and robotics will automate some repetitive plastering tasks, but skilled plasterers will remain necessary for varied sites, repairs, finishing, and complex work.

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 Plasterers and Stucco Masons? Nah. Still needs a human: 86/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/plasterers-and-stucco-masons/ (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.