US dataswitch to UK
Real Estate Sales Agents
preparing documents, representation contracts, purchase agreements, closing statements, deeds and leases, coordinating appointments to show homes to prospective buyers and answering clients' questions regarding construction work. 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: preparing documents, representation contracts, purchase agreements, closing statements, deeds and leases. That is a slice of tasks, not of you.
That slice is not coming back; the core of the job, acting as an intermediary in negotiations between buyers and sellers, stays yours. New tools, same person answering for it.
Your week, as this page understands it
Rent, buy, or sell property for clients. Perform duties such as study property listings, interview prospective clients, accompany clients to property site, discuss conditions of sale, and draw up real estate contracts. Includes agents who represent buyer. The job title says “real estate sales agents”. The real job is the part underneath: acting as an intermediary in negotiations between buyers and sellers. 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 real estate sales agents is not one task. It is 33 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is acting as an intermediary in negotiations between buyers and sellers, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 26%
- changing shape
- 28%
- staying human
- 46%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 40 out of 100 (34–45 allowing for uncertainty): partial exposure, across 33 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 real estate sales agents 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 2026-08-04. 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.
- One task scored differently between repeat runs, so its range on this page is wider. We would rather show the wobble than hide it.
- 5 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
8 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.
Preparing documents, representation contracts, purchase agreements, closing statements, deeds and leases
This is reading one thing and writing another: documents, representation contracts, purchase agreements, closing statements in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Prepare documents such as representation contracts, purchase agreements, closing statements, deeds, and leases.” (O*NET task statement)
How this row was scored
Exposure score: 81 out of 100 (77–85 allowing for uncertainty): very 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: Contracts, agreements and closing statements come from standard templates software fills accurately, with an agent responsible for the result.
The five ratings: output a model can produce 4/4 · 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.
Generating lists of properties that are compatible with buyers' needs and financial resources
This is reading one thing and writing another: lists of properties in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Generate lists of properties that are compatible with buyers' needs and financial resources.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 allowing for uncertainty): very 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: Matching properties to a buyer’s needs and budget is a search job software already does very 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 0/4 · how much data exists 4/4.
Comparing a property with similar properties that have recently sold to determine its competitive market price
This is reading one thing and writing another: a property in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Compare a property with similar properties that have recently sold to determine its competitive market price.” (O*NET task statement)
How this row was scored
Exposure score: 62 out of 100 (55–69 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: Comparing recent sales to price a home is data analysis software does well, though the property condition still needs seeing.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Coordinating appointments to show homes to prospective buyers
This is reading one thing and writing another: appointments in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Coordinate appointments to show homes to prospective buyers.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 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: Arranging viewing appointments is standard scheduling work.
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.
Changing shape
8 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.
Conferring with escrow companies, lenders
The software now makes the first pass at escrow companies, lenders, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Confer with escrow companies, lenders, home inspectors, and pest control operators to ensure that terms and conditions of purchase agreements are met before closing dates.” (O*NET task statement)
How this row was scored
Exposure score: 40 out of 100 (33–47 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Chasing lenders, inspectors and escrow to hit a closing date is coordination software can prompt but people complete.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Interviewing clients to determine what kinds of properties they are seeking
The software now makes the first pass at clients, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Interview clients to determine what kinds of properties they are seeking.” (O*NET task statement)
How this row was scored
Exposure score: 40 out of 100 (36–44 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Finding out what a buyer really wants happens in conversation with them.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Contacting previous clients for prospecting of referral business
The software now makes the first pass at previous clients, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Contact previous clients for prospecting of referral business.” (O*NET task statement)
How this row was scored
Exposure score: 53 out of 100 (46–60 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Reaching out to past clients can be drafted and scheduled by software, though referrals rest on the personal relationship.
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 2/4 · how much data exists 3/4.
Staying human
17 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.
Presenting purchase offers to sellers for consideration
The value here is that a specific person handles purchase offers and stands behind it. That is earned, not computed.
importance 5 · CoreSource: “Present purchase offers to sellers for consideration.” (O*NET task statement)
How this row was scored
Exposure score: 18 out of 100 (14–22 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Putting an offer to a seller is a live conversation where their reaction shapes what happens next.
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 3/4 · how much data exists 2/4.
Acting as an intermediary in negotiations between buyers and sellers
The value here is that a specific person handles an intermediary and stands behind it. That is earned, not computed.
importance 5 · CoreSource: “Act as an intermediary in negotiations between buyers and sellers, generally representing one or the other.” (O*NET task statement)
How this row was scored
Exposure score: 12 out of 100 (8–16 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Negotiating between buyer and seller depends on the trust each side places in the agent.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Promoting sales of properties through advertisements
This work happens in the physical world: sales of properties, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Promote sales of properties through advertisements, open houses, and participation in multiple listing services.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Ads and listings can be produced automatically, but open houses need someone at the property.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Show the other 23 tasks
Arranging for title searches to determine whether clients have clear property titles
shifting to AIThis is reading one thing and writing another: title searches in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Arrange for title searches to determine whether clients have clear property titles.” (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: Ordering a title search is an administrative step software can handle end to end.
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.
Answering clients' questions regarding construction work
shifting to AIThis is reading one thing and writing another: clients' questions regarding construction work in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Answer clients' questions regarding construction work, financing, maintenance, repairs, and appraisals.” (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: Answering common questions about financing, repairs and appraisals draws on well-documented knowledge software can supply.
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.
Contacting utility companies for service hookups to clients' property
shifting to AIThis is reading one thing and writing another: utility companies in, a record out. That is the shape today's tools are built for.
importance 3 · SupplementalSource: “Contact utility companies for service hookups to clients' property.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 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: Arranging utility hookups is routine administrative contact.
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.
Evaluating mortgage options to help clients obtain financing at the best prevailing rates and terms
shifting to AIThis is reading one thing and writing another: mortgage options in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Evaluate mortgage options to help clients obtain financing at the best prevailing rates and terms.” (O*NET task statement)
How this row was scored
Exposure score: 61 out of 100 (54–68 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: Comparing mortgage products against a client position is well-documented analysis software does 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 1/4 · how much data exists 4/4.
Investigating clients' financial and crediting status to determine eligibility for financing
changing shapeThe software now makes the first pass at clients' financial and crediting status, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · SupplementalSource: “Investigate clients' financial and credit status to determine eligibility for financing.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial 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: Checking a client financial and credit position is standard document and data checking.
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 1/4 · how much data exists 3/4.
Contacting property owners and advertise services to solicit property sales listings
changing shapeThe software now makes the first pass at property owners, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Contact property owners and advertise services to solicit property sales listings.” (O*NET task statement)
How this row was scored
Exposure score: 53 out of 100 (46–60 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Prospecting messages can be written and sent automatically, but winning a listing rests on the owner trusting the agent.
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 2/4 · how much data exists 3/4.
Advising sellers on how to make homes more appealing to potential buyers
changing shapeThe software now makes the first pass at sellers, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Advise sellers on how to make homes more appealing to potential buyers.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial 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: Advice on presenting a home well is documented and easily drafted, though it usually follows a look at the property.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Soliciting and compiling listings of available rental properties
changing shapeThe software now makes the first pass at listings of available rental properties, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · SupplementalSource: “Solicit and compile listings of available rental properties.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial 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: Compiling available rentals is list-building software does well, though the listings come from contacting owners.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Advising clients on market conditions
changing shapeThe software now makes the first pass at clients, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Advise clients on market conditions, prices, mortgages, legal requirements, and related matters.” (O*NET task statement)
How this row was scored
Exposure score: 46 out of 100 (39–53 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Market and mortgage information is well documented, but clients act on advice from someone they trust.
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 2/4 · how much data exists 3/4.
Reviewing property listings, trade journals and relevant literature and attending conventions, seminars and staff and association meetings
staying humanThis work happens in the physical world: property listings, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Review property listings, trade journals, and relevant literature, and attend conventions, seminars, and staff and association meetings, to remain knowledgeable about real estate markets.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Reading listings and journals is easy for software; conventions and association meetings mean turning up in person.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Reviewing plans for new construction with clients
staying humanThe value here is that a specific person handles plans and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Review plans for new construction with clients, enumerating and recommending available options and features.” (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: Going through construction plans with a client mixes document reading with an in-person discussion of choices.
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.
Arranging meetings between buyers and sellers when details of transactions
staying humanThe value here is that a specific person handles meetings and stands behind it. That is earned, not computed.
importance 3 · SupplementalSource: “Arrange meetings between buyers and sellers when details of transactions need to be negotiated.” (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: Setting up the meeting is scheduling, but the negotiation happening in it is the point.
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.
Appraising properties to determine loan values
staying humanThis work happens in the physical world: properties, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Appraise properties to determine loan values.” (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 same decision, made over and over; work that happens in the physical world; someone qualified has to answer for it.
The rating behind it: Formal appraisal for lending is reserved by law for a certified appraiser who has seen the property.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 3/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Securing construction or purchasing financing with own firm or mortgage company
staying humanThe rules require a named, qualified person to answer for construction, and that person cannot be a piece of software.
importance 3 · SupplementalSource: “Secure construction or purchase financing with own firm or mortgage company.” (O*NET task statement)
How this row was scored
Exposure score: 22 out of 100 (12–32 allowing for uncertainty): low exposure, medium confidence, and it moved between repeat runs, so the range is widened.
Why it sits in this group: someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Arranging mortgage finance is regulated advice in the UK and must come from an authorised person.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 3/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Conducting seminars and training sessions for sales agents to improve sales techniques
staying humanThis work happens in the physical world: seminars, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Conduct seminars and training sessions for sales agents to improve sales techniques.” (O*NET task statement)
How this row was scored
Exposure score: 20 out of 100 (13–27 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Running training sessions for other agents depends on being in the room with them.
The five ratings: output a model can produce 2/4 · 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 3/4.
Locating and appraising undeveloped areas for building sites
staying humanThis work happens in the physical world: undeveloped areas, in a real place. Software cannot follow it there.
importance 2 · SupplementalSource: “Locate and appraise undeveloped areas for building sites, based on evaluations of area market conditions.” (O*NET task statement)
How this row was scored
Exposure score: 19 out of 100 (12–26 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; someone qualified has to answer for it.
The rating behind it: Assessing undeveloped land means visiting it and forming a view a qualified valuer answers for.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Coordinating property closings, overseeing signing of documents and disbursement of funds
staying humanThis work happens in the physical world: property closings, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Coordinate property closings, overseeing signing of documents and disbursement of funds.” (O*NET task statement)
How this row was scored
Exposure score: 18 out of 100 (14–22 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Closings happen in a room with people signing documents and money moving.
The five ratings: output a model can produce 2/4 · 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 3/4.
Renting or leasing properties on behalf of clients
staying humanThis work happens in the physical world: properties, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Rent or lease properties on behalf of clients.” (O*NET task statement)
How this row was scored
Exposure score: 18 out of 100 (11–25 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Letting a property mixes standard paperwork with viewings and tenant meetings.
The five ratings: output a model can produce 2/4 · 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 3/4.
Developing networks of attorneys, mortgage lenders and contractors to whom clients
staying humanThe value here is that a specific person handles networks of attorneys, mortgage lenders and contractors and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Develop networks of attorneys, mortgage lenders, and contractors to whom clients may be referred.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (9–17 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Building a referral network is made of personal relationships with particular professionals.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Inspecting condition of premises and arranging for necessary maintenance or notifying owners of maintenance needs
staying humanThis work happens in the physical world: condition of premises, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Inspect condition of premises, and arrange for necessary maintenance or notify owners of maintenance needs.” (O*NET task statement)
How this row was scored
Exposure score: 11 out of 100 (7–15 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Judging the condition of a property means being on the premises.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Displaying commercial, industrial, agricultural and residential properties to clients and explaining their features
staying humanThis work happens in the physical world: commercial, industrial, agricultural and residential properties, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Display commercial, industrial, agricultural, and residential properties to clients and explain their features.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (6–14 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Showing a property to a client and pointing out its features means being there with them.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Accompanying buyers during visits to and inspections of property
staying humanThis work happens in the physical world: buyers during visits, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Accompany buyers during visits to and inspections of property, advising them on the suitability and value of the homes they are visiting.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high 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: Walking a buyer around a property is physical presence by definition.
The five ratings: output a model can produce 1/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Visiting properties to assess them before showing them to clients
staying humanThis work happens in the physical world: properties, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Visit properties to assess them before showing them to clients.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Visiting a property before showing it is presence by definition.
The five ratings: output a model can produce 1/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · 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
- $52,830a 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
- 193,370in 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: documents, representation contracts, purchase agreements, closing statements in, a record out. The rows above are exactly that shape: preparing documents, representation contracts, purchase agreements, closing statements, deeds and leases and generating lists of properties that are compatible with buyers' needs and financial resources. What it cannot do is be trusted in person, which is what an intermediary runs on: someone specific doing it and standing behind it. 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. Preparing documents, representation contracts, purchase agreements, closing statements, deeds and leases is going; acting as an intermediary in negotiations between buyers and sellers is not.
So, given all that: 26% of this job's task weight sits in rows the software is already learning, 28% in rows that change shape rather than disappear, and 46% in rows it is nowhere near. That is the position, measured across 33 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 (acting as an intermediary in negotiations between buyers and sellers) 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 acting as an intermediary in negotiations between buyers and sellers, 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 real estate sales agents (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was real estate brokers: only about 7% of its durable work is work you already do and there are far fewer of those jobs than of yours. Your own job splits about 26/74: 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 “present purchase offers to sellers for consideration”, 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.
Real Estate Brokers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already act as an intermediary in negotiations between buyers and sellers, generally representing one…, and their equivalent is to act as an intermediary in negotiations between buyers and sellers over property prices…. Across both published task lists that is about 7% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 7% of the durable side of that job. That is a different job, not a next step. And it is a narrow door: about 46,100 of those jobs against 193,370 of yours (OEWS May 2025), 24% as many seats.
Property, Real Estate, and Community Association Managers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already display commercial, industrial, agricultural, and residential properties to clients and explain their features, and their equivalent is to manage and oversee operations, maintenance, administration, and improvement of commercial, industrial, or residential…. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step.
Agents and Business Managers of Artists, Performers, and Athletes
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already advise clients on market conditions, prices, mortgages, legal requirements, and related matters, and their equivalent is to advise clients on financial and legal matters. 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. And it is a narrow door: about 12,620 of those jobs against 193,370 of yours (OEWS May 2025), 7% as many seats.
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: 26% of its task weight, across 33 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 Estate agents and auctioneers 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 Estate agents and auctioneers and Property, housing and estate managers. 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 real estate sales agents, 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 26% 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 real estate sales agents. 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 real estate sales agents launches. Nothing else.
That did not look like an email address, so nothing was saved. Have another go below.
We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.
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 Real Estate Sales Agents?
- Not as a job, but it is already doing parts of the work. Across the 33 official task statements scored for Real Estate Sales Agents (United States, SOC 41-9022), 26% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 40 out of 100 (range 34–45, 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 “Real Estate Sales Agents” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Generate lists of properties that are compatible with buyers' needs and financial resources” (83/100, very high); “Prepare documents such as representation contracts, purchase agreements, closing statements, deeds, and leases” (81/100, very high); “Arrange for title searches to determine whether clients have clear property titles” (75/100, 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 “Real Estate Sales Agents” stay human?
- About 46% 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: “Visit properties to assess them before showing them to clients” (0/100, minimal); “Accompany buyers during visits to and inspections of property, advising them on the suitability and value of the homes they are visiting” (0/100, minimal); “Display commercial, industrial, agricultural, and residential properties to clients and explain their features” (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 “Real Estate Sales Agents” do about AI?
- Start from the ledger rather than the headline: 26% of this job's weighted core work is exposed, and roughly 46% 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 Real Estate Sales Agents 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 33 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
About the data on this page
- One task scored differently between repeat runs, so its range on this page is wider. We would rather show the wobble than hide it.
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 5 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.