AI Automation Index

Will AI Replace Landscape Architects?

Task-level automation exposure for Landscape Architects: 19 O*NET tasks scored against their work activities, plus the simulator.

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Developed & audited by Gini Loh

Automation Exposure

53% weighted task index

19 of 19 tasks scored

Median Salary

$79,870 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Low

19,600 people hold this job — size, not growth

Projected 2025–35

+4.4% employment change

1,700 openings a year · BLS line item

Pay by state

BLS OEWS publishes 42 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$50,960 – $101,220

Highest medians

Alabama $101,220

California $98,380

Tennessee $95,250

New Jersey $95,020

Utah $94,430

Lowest medians

Puerto Rico $50,960

Arkansas $60,840

Nebraska $62,170

Ohio $63,790

Oklahoma $64,370

State figures come from the 17-1012 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.

Automation potential 53%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 0%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 50%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 0%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 0%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 0/100 Low

O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.

Constituent Task Mix

19 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 31%

6 tasks

Medium exposure (≥ 35%) 53%

10 tasks

Low exposure (below 35%) 16%

3 tasks

How would you survive?

Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.

Simulate Upskilling →

Emerging & rewritten tasks

Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.

New 08/2025 · Occupational Expert

Develop and facilitate community engagement campaigns and workshops to better understand the community's needs.
New 08/2025 · Occupational Expert

Prepare ecological restoration or mitigation design plans to enhance or restore habitats.
New 05/2025 · AI/SME

Use drone technology to survey large areas and gather accurate topographical data.

Constituent Tasks

#20369 · Core · 50% automatable

Confer with clients, engineering personnel, or architects on landscape projects.

interpersonal — Discussing designs with clients needs human persuasion

Discuss designs or plans with clients.

#20371 · Core · 65% automatable

Analyze data on conditions such as site location, drainage, or structure location for environmental reports or landscaping plans.

data analysis — Analyzes survey/physical data; human checks quality

Analyze physical, survey, or geographic data.

#20373 · Core · 22% automatable

Inspect landscape work to ensure compliance with specifications, evaluate quality of materials or work, or advise clients or construction personnel.

visual inspection — Physical site verification against specs is human

Inspect facilities or sites to determine if they meet specifications or standards.

#20370 · Core · 60% automatable

Prepare site plans, specifications, or cost estimates for land development.

visual inspection — Generates maps; cartographic accuracy and standards human

Create maps.

#20375 · Core · 55% automatable

Integrate existing land features or landscaping into designs.

decision support — AI proposes green features; engineer owns design decisions

Incorporate green features into the design of structures or facilities.

#19597 · Core · 55% automatable

Collaborate with architects or related professionals on whole building design to maximize the aesthetic features of structures or surrounding land and to improve energy efficiency.

interpersonal — Conferring with technical staff on plans is relational work

Confer with technical personnel to prepare designs or operational plans.

#18470 · Core · 50% automatable

Prepare graphic representations or drawings of proposed plans or designs.

visual inspection — Generates structure graphics; survey accuracy human

Create graphical representations of structures or landscapes.

#20378 · Core · 22% automatable

Inspect proposed sites to identify structural elements of land areas or other important site information, such as soil condition, existing landscaping, or the proximity of water management facilities.

visual inspection — Physical site verification against specs is human

Inspect facilities or sites to determine if they meet specifications or standards.

#20380 · Core · 55% automatable

Collaborate with estimators to cost projects, create project plans, or coordinate bids from landscaping contractors.

interpersonal — Conferring with technical staff on plans is relational work

Confer with technical personnel to prepare designs or operational plans.

#19598 · Core · 55% automatable

Create landscapes that minimize water consumption such as by incorporating drought-resistant grasses or indigenous plants.

decision support — AI proposes green features; engineer owns design decisions

Incorporate green features into the design of structures or facilities.

#20379 · Core · 72% automatable

Develop planting plans to help clients garden productively or to achieve particular aesthetic effects.

text generation — Detailed work plans drafted from specifications

Prepare detailed work plans.

#20376 · Core · 30% automatable

Manage the work of subcontractors to ensure quality control.

interpersonal — Supervising engineers needs accountability and motivation

Supervise engineering or other technical personnel.

#20374 · Core · 55% automatable

Present project plans or designs to public stakeholders, such as government agencies or community groups.

text generation — Explanatory content drafted; public engagement human

Explain project details to the general public.

#20372 · Core · 62% automatable

Develop marketing materials, proposals, or presentations to generate new work opportunities.

text generation — Campaign content and analysis drafted; human executes strategy

Perform marketing activities.

#20381 · Core · 50% automatable

Prepare conceptual drawings, graphics, or other visual representations of land areas to show predicted growth or development of land areas over time.

visual inspection — Generates structure graphics; survey accuracy human

Create graphical representations of structures or landscapes.

#19600 · Core · 56% automatable

Identify and select appropriate sustainable materials for use in landscape designs, such as recycled wood or recycled concrete boards for structural elements or recycled tires for playground bedding.

decision support — Project material selection needs spec and site judgment

Select project materials. Incorporate green features into the design of structures or facilities.

#20377 · Core · 80% automatable

Research latest products, technology, or design trends to stay current in the field.

information retrieval — AI tracks technical updates; human validates depth

Update technical knowledge.

#19599 · Core · 35% automatable

Design and integrate rainwater harvesting or gray and reclaimed water systems to conserve water into building or land designs.

decision support — AI aids system design; site engineering and hydrology human

Design water conservation systems.

#20382 · Core · 70% automatable

Provide follow-up consultations for clients to ensure landscape designs are maturing or developing as planned.

information retrieval — Product-use advice is largely informational with review

Advise customers on the use of products or services.

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Community Sentiment

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Method

How this was scored

1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.

Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast

See the full method →

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