Will AI replace Segmental Pavers?
AI reaches little of this job’s work.
8/100
Low exposure
More exposed to AI than 17% of US workers.
- AI already used in
- 0% of the work
- As AI tools mature: up to
- 16% of the work
What the job involves
Lay out, cut, and place segmental paving units. Includes installers of bedding and restraining materials for the paving units.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Within reach(2)
- Design paver installation layout pattern and create markings for directional references of joints and stringlines.
- Discuss the design with the client.
Out of reach(10)
- Prepare base for installation by removing unstable or unsuitable materials, compacting and grading the soil, draining or stabilizing weak or saturated soils and taking measures to prevent water penetration and migration of bedding sand.
- Compact bedding sand and pavers to finish the paved area, using a plate compactor.
- Set pavers, aligning and spacing them correctly.
- Supply and place base materials, edge restraints, bedding sand and jointing sand.
- Sweep sand into the joints and compact pavement until the joints are full.
and 5 more
Also called
Paver Installer · Paving Stone Installer · Paver · Segmental Wall Installer · Concrete Pavement Installer · Interlocking Concrete Pavement Installer · Segmental Paver Installer · Cutter
Related jobs
What these numbers mean
The score is the share of this job’s work, weighted by how important and frequent each task is, that AI could do in half the time: tasks an AI model could do alone count in full, tasks that need software built on AI count half.
“AI already used” is the share of the work in tasks where people are recorded using AI today. “As AI tools mature” counts every task AI could halve, with or without extra software.
The percentile compares the score with every job’s, weighted by how many people in the US do each one. Exposure means AI could change how the work is done, not that the job goes away. These are estimates for the typical job, not predictions.
Sources
- O*NET 31.0 Database, U.S. Department of Labor, Employment and Training Administration
- GPTs are GPTs: Labor market impact potential of LLMs (task labels), Eloundou, Manning, Mishkin & Rock (2023), OpenAI and University of Pennsylvania
- Anthropic Economic Index: labor market impacts (task penetration), Anthropic
- Occupational Employment and Wage Statistics, May 2025 (national and metropolitan areas), U.S. Bureau of Labor Statistics