US dataswitch to UK
Landscape Architects
conferring with clients, engineering personnel or architects on landscape projects, preparing graphic representations or drawings of proposed plans or designs and inspecting proposed sites to identify structural elements of land areas or other important site information. If that's your week, this page is about your job.
The honest answer
AI is already taking a real slice of the routine work here: analyzing data on conditions, site location, drainage or structure location for environmental reports or landscaping plans. That is a slice of tasks, not of you.
That slice is not coming back; the core of the job, inspecting landscape work to ensure compliance with specifications, stays yours. New tools, same person answering for it.
Your week, as this page understands it
Plan and design land areas for projects such as parks and other recreational facilities, airports, highways, hospitals, schools, land subdivisions, and commercial, industrial, and residential sites. The job title says “landscape architects”. The real job is the part underneath: inspecting landscape work to ensure compliance with specifications. That is the thing someone has to be right about.
The exposed part of this job is specific, and we won’t pretend it is coming back. But landscape architects is not one task. It is 19 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is inspecting landscape work to ensure compliance with specifications, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 31%
- changing shape
- 26%
- staying human
- 43%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 41 out of 100 (35–48 allowing for uncertainty): partial exposure, across 19 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.
How we know this
What is measured: Every published task statement for landscape architects is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.
How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.
Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.
Your job, task by task
These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.
- 3 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
Shifting to AI
6 tasksTasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.
Analyzing data on conditions, site location, drainage or structure location for environmental reports or landscaping plans
This is reading one thing and writing another: data in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Analyze data on conditions such as site location, drainage, or structure location for environmental reports or landscaping plans.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Analyzing drainage, location and site data is number work software does well before a designer signs it off.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Creating landscapes that minimize water consumption
This is reading one thing and writing another: landscapes in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Create landscapes that minimize water consumption such as by incorporating drought-resistant grasses or indigenous plants.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Choosing drought-tolerant grasses and native plants for a region draws on well-published plant data software searches quickly.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Collaborating with estimators to cost projects
This is reading one thing and writing another: estimators in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Collaborate with estimators to cost projects, create project plans, or coordinate bids from landscaping contractors.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Pulling together costs, schedules and contractor bids is document and spreadsheet work software handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Developing marketing materials, proposals or presentations to generate new work opportunities
This is reading one thing and writing another: materials, proposals or presentations in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Develop marketing materials, proposals, or presentations to generate new work opportunities.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Proposals, brochures and pitch decks are written material software produces quickly to a good standard.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Changing shape
5 tasksTasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.
Preparing site plans, specifications or cost estimates for land development
The software now makes the first pass at site plans, specifications or cost estimates, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Prepare site plans, specifications, or cost estimates for land development.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Software drafts plans and cost estimates, but a licensed designer normally has to be involved in what gets submitted.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing graphic representations or drawings of proposed plans or designs
The software now makes the first pass at graphic representations, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Prepare graphic representations or drawings of proposed plans or designs.” (O*NET task statement)
How this row was scored
Exposure score: 50 out of 100 (43–57 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Software produces attractive concept images quickly, but construction-quality drawings still need substantial work from the designer.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Developing planting plans to help clients garden productively or to achieve particular aesthetic effects
The software now makes the first pass at plans, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Develop planting plans to help clients garden productively or to achieve particular aesthetic effects.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Software can build a planting list, but matching it to one client's taste and garden usually needs reworking.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Staying human
8 tasksTasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.
Conferring with clients, engineering personnel or architects on landscape projects
The value here is that a specific person handles clients, engineering personnel or architects and stands behind it. That is earned, not computed.
importance 5 · CoreSource: “Confer with clients, engineering personnel, or architects on landscape projects.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Software can prepare and summarize the material, but the give-and-take with a client or engineer still needs a person.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Inspecting landscape work to ensure compliance with specifications
This work happens in the physical world: landscape work, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Inspect landscape work to ensure compliance with specifications, evaluate quality of materials or work, or advise clients or construction personnel.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (2–10 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Checking that planting and paving were actually built to specification means standing on the site and looking at it.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Collaborating with architects or related professionals on whole building design to maximize the aesthetic features of structures or surrounding land and to improve energy efficiency
The value here is that a specific person handles architects and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “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.” (O*NET task statement)
How this row was scored
Exposure score: 23 out of 100 (16–30 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Joint design work with architects depends on live back-and-forth, even though software can produce options and energy calculations.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Show the other 9 tasks
Researching latest products, technology or designing trends to stay current in the field
shifting to AIThis is reading one thing and writing another: latest products, technology or designing trends in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Research latest products, technology, or design trends to stay current in the field.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (76–90 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Keeping up with new products and design trends is searching and summarizing, which software does quickly and broadly.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Identifying and selecting appropriate sustainable materials for use in landscape designs
shifting to AIThis is reading one thing and writing another: appropriate sustainable materials in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “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.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Recycled and sustainable material options are well documented, so software can shortlist suitable choices for a design.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing conceptual drawings, graphics or other visual representations of land areas to show predicted growth or development of land areas over time
changing shapeThe software now makes the first pass at conceptual drawings, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Prepare conceptual drawings, graphics, or other visual representations of land areas to show predicted growth or development of land areas over time.” (O*NET task statement)
How this row was scored
Exposure score: 44 out of 100 (37–51 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Software can generate growth visuals, though showing how one particular site will mature still needs the designer's judgment.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Designing and integrating rainwater harvesting or gray and reclaimed water systems to conserve water into building or land designs
changing shapeThe software now makes the first pass at rainwater, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 3 · CoreSource: “Design and integrate rainwater harvesting or gray and reclaimed water systems to conserve water into building or land designs.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Rainwater and gray-water system sizing follows published methods, but a qualified professional normally has to stand behind the design.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Integrating existing land features or landscaping into designs
staying humanThe ratings behind this row put land features well outside what today's tools can do on their own.
importance 4 · CoreSource: “Integrate existing land features or landscaping into designs.” (O*NET task statement)
How this row was scored
Exposure score: 33 out of 100 (26–40 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Software can suggest how to work with existing trees and slopes, though the decisive feel for a site comes from visiting it.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Presenting project plans or designs to public stakeholders
staying humanThe value here is that a specific person handles project plans and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Present project plans or designs to public stakeholders, such as government agencies or community groups.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Slides and scripts are easy to prepare, but facing a community meeting and answering questions is a person's job.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Providing follow-up consultations for clients to ensure landscape designs are maturing or developing
staying humanThis work happens in the physical world: follow-up consultations, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Provide follow-up consultations for clients to ensure landscape designs are maturing or developing as planned.” (O*NET task statement)
How this row was scored
Exposure score: 11 out of 100 (4–18 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Checking whether planting is establishing as intended means going back to the site and talking it through with the client.
The five ratings: output a model can produce 1/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Managing the work of subcontractors to ensure quality control
staying humanThis work happens in the physical world: the work of subcontractors, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Manage the work of subcontractors to ensure quality control.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (3–17 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Keeping subcontractors to standard means being on site and holding people to their work.
The five ratings: output a model can produce 1/4 · needs a body in a room 2/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Inspecting proposed sites to identify structural elements of land areas or other important site information
staying humanThis work happens in the physical world: proposed sites, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “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.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (3–11 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Judging soil, existing planting and nearby water features means walking the site in person.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
What this job pays, and how many people do it
- Median pay
- $79,870a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
- People doing this job
- 19,600in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)
What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.
Why this is shifting
The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: site plans, specifications or cost estimates in, a record out. The rows above are exactly that shape: analyzing data on conditions, site location and creating landscapes that minimize water consumption. What it cannot do is be there in the room, and that is still where landscape work gets done. Which is why this page talks about your tasks changing, not your job ending.
Your move
Over a pint: what I’d tell you if you were my friend
Your week is splitting in two, and which half fills it is the whole question. Analyzing data on conditions, site location, drainage or structure location for environmental reports or landscaping plans is going; inspecting landscape work to ensure compliance with specifications is not.
So, given all that: 31% of this job's task weight sits in rows the software is already learning, 26% in rows that change shape rather than disappear, and 43% in rows it is nowhere near. That is the position, measured across 19 scored tasks. It is not a forecast about you.
The occupation is an average and you are not, so the first job below is finding out where your own week actually sits.
This week: one thing
Print the task ledger above and put your own hours next to each row. Roughly, in pen, in one sitting. Then look at which group your hours actually pile up in. Twenty minutes, this week.
- What you end up holding
- your own week, on one page, sorted into what is shifting and what is not
- How long it takes
- about twenty minutes
If printing it isn’t practical: Read the rows off this page and write the same list on the back of an envelope. Same twenty minutes, same page, and it works just as well said out loud to someone who knows the job. The point is your hours next to the rows, not the paper it is on.
Over the next 90 days
Volunteer toward the durable end, visibly. Over the next ninety days put your hand up for the work in the bottom group (inspecting landscape work to ensure compliance with specifications) and let people see you doing it. Not a new project: the same job, with your mix deliberately tilted. The point is that when the rota or the reorganisation comes, the version of you people picture is the one doing the part that stays.
Over the next 12 months
Claim a specialism at the durable end and let the other end go. Over a year, deliberately become the person who handles inspecting landscape work to ensure compliance with specifications, and deliberately stop being the first choice for the rows in the top group. That trade costs something, because the exposed work is often the comfortable work. Decide it on purpose rather than by drift. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.
The roads out of here, and why I am not sending you down them
I looked at the obvious moves out of this job, and here is what I found.
I checked the 12 nearest US occupations to landscape architects (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was cost estimators: only about 5% of its durable work is work you already do and it is under the same pressure this job is. Your own job splits about 31/69: that share of the list sits in the top exposure band and the rest does not. On this evidence the honest move is inside the job rather than out of it. Become the person who owns “confer with clients, engineering personnel, or architects on landscape projects”, and let the exposed end go.
How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.
3 moves I checked and rejected
These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.
Cost Estimators
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already confer with clients, engineering personnel, or architects on landscape projects, and their equivalent is to confer with engineers, architects, owners, contractors, and subcontractors on changes and adjustments to…. Across both published task lists that is about 5% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 5% of the durable side of that job. That is a different job, not a next step. I will not move you off one melting floe onto another: 67% of its own task list already scores in the top exposure band (63/100 in this release), so the same software is eating it.
Urban and Regional Planners
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already present project plans or designs to public stakeholders, and their equivalent is to advocate sustainability to community groups, government agencies, the general public, or special interest…. Across both published task lists that is about 3% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step.
Managers, All Other
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already manage the work of subcontractors to ensure quality control, and their equivalent is to supervise employees or subcontractors to ensure quality of work or adherence to safety…. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% of the durable side of that job. That is a different job, not a next step.
What I’d stop worrying about
A friend tells you what not to spend fear on. This is that list.
The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 31% of its task weight, across 19 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The whole-job doom story
Nothing on this page says this job ends. It says the mix inside it moves. Half the rows above are unchanged or changing shape, and the plan is about which half your week sits in. That is a very different problem, and a solvable one.
Panic-buying a course
Do the twenty-minute sorting exercise first. Most people who buy a course before they have done it buy the wrong one, and the free services listed below will tell you the same thing without charging for it.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which Architects is the closest. The pay and employment figures are not directly comparable, and we do not average them together.
Switch to the United Kingdom page →partial match
The other groups this work is counted across:
In UK official statistics this job is counted as Architects and Gardeners and landscape gardeners. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.
Your route through this
Where to go next, and what it costs
Free, and complete
The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.
Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
Free
No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for landscape architects, and we are not going to point you at the nearest one and call it a fit.
There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 31% of the work on this page is already inside what they can do.
7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.
The AI Authority is a general community about working with AI, not a course for landscape architects. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.
Noted, and thank you. We’ll email you if a Space for landscape architects launches. Nothing else.
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No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.
Questions people ask about this job
- Will AI replace Landscape Architects?
- Not as a job, but it is already doing parts of the work. Across the 19 official task statements scored for Landscape Architects (United States, SOC 17-1012), 31% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 41 out of 100 (range 35–48, band: partial). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
- Which tasks in “Landscape Architects” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Research latest products, technology, or design trends to stay current in the field” (83/100, very high); “Develop marketing materials, proposals, or presentations to generate new work opportunities” (75/100, high); “Create landscapes that minimize water consumption such as by incorporating drought-resistant grasses or indigenous plants” (66/100, high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
- Which tasks in “Landscape Architects” stay human?
- About 43% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Inspect landscape work to ensure compliance with specifications, evaluate quality of materials or work, or advise clients or construction personnel” (6/100, minimal); “Inspect proposed sites to identify structural elements of land areas or other important site information, such as soil condition, existing landscaping, or th…” (7/100, minimal); “Manage the work of subcontractors to ensure quality control” (10/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
- What should someone working in “Landscape Architects” do about AI?
- Start from the ledger rather than the headline: 31% of this job's weighted core work is exposed, and roughly 43% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
- How is the AI exposure score for Landscape Architects calculated?
- Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 19 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.
Where these numbers come from
Worth knowing about these figures
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 3 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
- Task statements
- onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
- Task weights
- onet-db (im-rt)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.
The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.
The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.
Using these figures?
Cite this
Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.
Plain text
Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).
BibTeX
@misc{collab365futureproof2026q41,
title = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
author = {{Collab365}},
year = {2026},
url = {https://futureproof.collab365.com/data/2026-q4.1},
note = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}Data as of release 2026-q4.1, published . Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.