How exposed to AI is the job of Segmental Pavers?

6.7% of the weighted task load of Segmental Pavers is exposed, meaning work current AI systems can produce with little structural friction. A further 3.5% is assisted work and 89.8% is untouched. That places it 8th out of 923 occupations, rank 851, in release v2026.Q3 of the Task Exposure Index.

Will AI replace Segmental Pavers?

The index does not measure displacement. It measures what current AI systems can produce and what stands in the way. Whether exposed work becomes a lost job depends on firm economics, regulation and organisational inertia, none of which this index models.

Which tasks of a Segmental Pavers are most exposed to AI?

Of 12 tasks O*NET records for this occupation, 1 are exposed, 0 assisted and 11 untouched. The full task-by-task breakdown is published on this page.

Occupation · SOC 47-4091.00 · Job Zone 2

AI exposure: Segmental Pavers

Lay out, cut, and place segmental paving units. Includes installers of bedding and restraining materials for the paving units.

Reading this score

computed

Segmental Pavers is among the least exposed occupations measured, at 6.7% of weighted task load, rank 851 of 923. 89.8% of this job is work current AI systems cannot produce at all. That is not a statement about skill or value. It is a statement about what these systems can and cannot do.

What holds the line here is embodiment. Across this occupation's 12 tasks it averages 2.62 out of 3, the highest of the five friction dimensions. In plain terms, the work has to happen in physical space. A language model cannot move matter. Until the robotics to do this work is both good enough and cheap enough to deploy widely, capability in software does not reach it.

The most exposed thing this job does is Discuss the design with the client, at 66.7%. The least is Cement the edges of the paved area, at 0.0%. A gap of 66.7% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.

Within construction and extraction occupations, this one is more exposed than most. The median across the 61 roles in the group is 5.0%, and only 25 of them score higher than this. Occupational families are not uniform, and the spread inside them is often wider than the gap between them.

What would move this score. Of 12 tasks, 1 are currently banded exposed, 0 assisted and 11 untouched. For that distribution to shift materially would take robotics cheap and reliable enough to deploy at scale, not a better language model. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.

Where the score comes from

judged

Every task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.

Dimension	Mean	Scale
Capability	0.42	0-4
Embodiment	2.62	0-3
Presence	0.08	0-3
Accountability	0.62	0-3
Context	0.88	0-3
Verification cost	1.12	0-3

Task by task

12 tasks, O*NET 31.0

Task	Exposed	Assisted	Untouched	Importance	Band
Discuss the design with the client.	66.7%	33.3%	0.0%	4.26	exposed
Design paver installation layout pattern and create markings for directional references of joints and stringlines.	15.8%	9.2%	75.0%	3.95	untouched
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.	0.0%	0.0%	100.0%	4.37	untouched
Supply and place base materials, edge restraints, bedding sand and jointing sand.	0.0%	0.0%	100.0%	4.35	untouched
Set pavers, aligning and spacing them correctly.	0.0%	0.0%	100.0%	4.20	untouched
Sweep sand into the joints and compact pavement until the joints are full.	0.0%	0.0%	100.0%	4.10	untouched
Screed sand level to an even thickness, and recheck sand exposed to elements, raking and rescreeding if necessary.	0.0%	0.0%	100.0%	4.08	untouched
Cut paving stones to size and for edges, using a splitter and a masonry saw.	0.0%	0.0%	100.0%	4.05	untouched
Compact bedding sand and pavers to finish the paved area, using a plate compactor.	0.0%	0.0%	100.0%	3.98	untouched
Sweep sand from the surface prior to opening to traffic.	0.0%	0.0%	100.0%	3.89	untouched
Resurface an outside area with cobblestones, terracotta tiles, concrete or other materials.	0.0%	0.0%	100.0%	3.25	untouched
Cement the edges of the paved area.	0.0%	0.0%	100.0%	3.16	untouched

Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean. 1 task(s) lacked a usable O*NET weight and are shown but excluded from the weighting.

Occupations either side of this one

The four closest scores in the same occupational family, then the four closest anywhere in the index.

Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.

What this means in practice

Most of this work is not reachable by current systems, so the immediate pressure is on the administrative edges of the role rather than its core: the scheduling, the reporting, the written records. That is where time is recovered.