# Cement Masons and Concrete Finishers

> Smooth and finish surfaces of poured concrete, such as floors, walks, sidewalks, roads, or curbs using a variety of hand and power tools. Align forms for sidewalks, curbs, or gutters; patch voids; and use saws to cut expansion joints.

- **SOC code:** 47-2051.00
- **Canonical URL:** https://singulariki.com/roles/role-47-2051-00
- **Also known as:** Cement Finisher, Cement Mason, Concrete Finisher, Finisher, Concrete Mason, Mason, Cement Gun Operator, Cement Mason Concrete Finisher
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Check the forms that hold the concrete to see that they are properly constructed.
- Set the forms that hold concrete to the desired pitch and depth, and align them.
- Spread, level, and smooth concrete, using rake, shovel, hand or power trowel, hand or power screed, and float.
- Monitor how the wind, heat, or cold affect the curing of the concrete throughout the entire process.
- Mold expansion joints and edges, using edging tools, jointers, and straightedge.
- Signal truck driver to position truck to facilitate pouring concrete, and move chute to direct concrete on forms.
- Direct the casting of the concrete and supervise laborers who use shovels or special tools to spread it.
- Produce rough concrete surface, using broom.
- Apply hardening and sealing compounds to cure surface of concrete, and waterproof or restore surface.
- Operate power vibrator to compact concrete.
- Wet surface to prepare for bonding, fill holes and cracks with grout or slurry, and smooth, using trowel.
- Install anchor bolts, steel plates, door sills and other fixtures in freshly poured concrete or pattern or stamp the surface to provide a decorative finish.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Manual Dexterity _(ability)_
- Trunk Strength _(ability)_
- English Language _(knowledge)_
- Multilimb Coordination _(ability)_
- Near Vision _(ability)_
- Building and Construction _(knowledge)_
- Arm-Hand Steadiness _(ability)_
- Control Precision _(ability)_
- Extent Flexibility _(ability)_
- Monitoring _(essential_skill)_
- Problem Sensitivity _(ability)_
- Deductive Reasoning _(ability)_

**Skills in demand:**
- English Language _(Common Skill)_
- Visualization _(Specialized Skill)_
- Information Ordering _(Specialized Skill)_
- Deductive Reasoning _(Common Skill)_
- Time Management _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Finger Dexterity _(Common Skill)_
- Mathematics _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Depth Perception _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Complex Problem Solving _(Common Skill)_

**Tools & technology:**
- ACT Contractors Forms
- ADAPT-Modeler
- Hard Dollar HD Project Estimating
- HIPERPAV
- LogicSphere Firstmix
- Maxwell Systems Quest Estimator
- National Concrete & Masonry Estimator
- Shilstone seeMIX
- Sirus GT Construction Accounting
- Tradesman's Software Master Estimator

## AI exposure & outlook

- **AI task-overlap index:** 1st percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 2nd percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 3rd percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 3rd percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 86th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 1.8% growth (About average); 14.3k annual openings; 206.7k → 210.4k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $54,660; 205,230 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 30% automation, 58% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** learning.

**Tasks most handed to AI here:**
- Monitor how the wind, heat, or cold affect the curing of the concrete throughout the entire process. _(0.9% of measured AI use; learning)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me monitor how the wind, heat, or cold affect the curing of the concrete throughout the entire process.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-47-2051-00_