US dataswitch to UK
Morticians, Undertakers, and Funeral Arrangers
overseeing the preparation and care of the remains of people, closing caskets and leading funeral corteges to churches or burial sites and providing information on funeral service options. If that's your week, this page is about your job.
The honest answer
AI changes the edges of this job, not the middle: overseeing the preparation and care of the remains of people is work software can't reach.
What shifts is contacting cemeteries to schedule the opening and closing of graves: the overhead at the edges, not the middle you trained for.
Your week, as this page understands it
Perform various tasks to arrange and direct individual funeral services, such as coordinating transportation of body to mortuary, interviewing family or other authorized person to arrange details, selecting pallbearers, aiding with the selection of officials for religious rites, and providing transportation for mourners. The job title says “morticians”, “undertakers” or “funeral arrangers”: officially one job, several names. The real job is the part underneath: overseeing the preparation and care of the remains of people. 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 morticians, undertakers, and funeral arrangers is not one task. It is 22 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is overseeing the preparation and care of the remains of people, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 14%
- changing shape
- 14%
- staying human
- 72%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 23 out of 100 (19–29 allowing for uncertainty): low exposure, across 22 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 morticians, undertakers, and funeral arrangers 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.
- 4 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
3 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.
Contacting cemeteries to schedule the opening and closing of graves
This is reading one thing and writing another: cemeteries in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Contact cemeteries to schedule the opening and closing of graves.” (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: Booking a grave opening with a cemetery is routine scheduling that software can handle.
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.
Arranging for clergy members to perform needed services
This is reading one thing and writing another: clergy members in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Arrange for clergy members to perform needed services.” (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: Booking a minister for a service is routine coordination.
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.
Maintaining financial records, order merchandise or preparing accounts
This is reading one thing and writing another: financial records, order merchandise or preparing accounts in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Maintain financial records, order merchandise, or prepare accounts.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 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: Keeping the books and ordering stock is standard business record-keeping that software does well.
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.
Changing shape
3 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.
Planning, scheduling or coordinating funerals, burials or cremations, arranging details
The software now makes the first pass at funerals, burials or cremations, arranging details, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Plan, schedule, or coordinate funerals, burials, or cremations, arranging details such as floral delivery or the time and place of services.” (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: Coordinating times, flowers and services is scheduling work that software organizes well.
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.
Providing or arranging transportation between sites for the remains
The software now makes the first pass at transportation, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Provide or arrange transportation between sites for the remains, mourners, pallbearers, clergy, or flowers.” (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: Arranging cars for the family, clergy and flowers is scheduling and booking work software handles.
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.
Arranging for pallbearers or informing pallbearers or honorary groups of their duties
The software now makes the first pass at pallbearers, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Arrange for pallbearers or inform pallbearers or honorary groups of their duties.” (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: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: Lining up pallbearers and telling them what to do is routine coordination and instruction.
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 2/4.
Staying human
16 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.
Obtaining information needed to complete legal documents
The rules require a named, qualified person to answer for information, and that person cannot be a piece of software.
importance 5 · CoreSource: “Obtain information needed to complete legal documents, such as death certificates or burial permits.” (O*NET task statement)
How this row was scored
Exposure score: 36 out of 100 (29–43 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Death certificates and burial permits are standard forms, so software can gather and fill most of the detail.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 2/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Consulting with families or friends of the deceased to arrange funeral details
This work happens in the physical world: families, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Consult with families or friends of the deceased to arrange funeral details, such as obituary notice wording, casket selection, or plans for services.” (O*NET task statement)
How this row was scored
Exposure score: 9 out of 100 (2–16 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: Families arranging a funeral need someone sitting with them; the choices follow from a personal conversation.
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 3/4 · how much data exists 2/4.
Overseeing the preparation and care of the remains of people
This work happens in the physical world: the preparation, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Oversee the preparation and care of the remains of people who have died.” (O*NET task statement)
How this row was scored
Exposure score: 4 out of 100 (0–11 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: Overseeing the care of a body means being present in the preparation room.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 2/4 · needs to be trusted in the moment 1/4 · how much data exists 1/4.
Offering counsel and comfort to bereaved families or friends
This work happens in the physical world: counsel, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Offer counsel and comfort to bereaved families or friends.” (O*NET task statement)
How this row was scored
Exposure score: 5 out of 100 (1–9 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: Comforting a grieving family is the work itself, and it needs a person in the room.
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 4/4 · how much data exists 1/4.
Show the other 12 tasks
Informing survivors of benefits for which they may be eligible
staying humanThe value here is that a specific person handles survivors of benefits and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Inform survivors of benefits for which they may be eligible.” (O*NET task statement)
How this row was scored
Exposure score: 39 out of 100 (32–46 allowing for uncertainty): low 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: Benefit rules are published, so software can identify entitlements, but a grieving family needs it explained by someone.
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 2/4 · how much data exists 3/4.
Providing information on funeral service options
staying humanThis work happens in the physical world: information, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Provide information on funeral service options, products, or merchandise, and maintain a casket display area.” (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 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: Product information is easy to present, but families expect to be walked through options and to see the caskets.
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 2/4 · how much data exists 3/4.
Directing preparations and shipment of bodies for out-of-state burial
staying humanThis work happens in the physical world: preparations, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Direct preparations and shipment of bodies for out-of-state burial.” (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: Shipping paperwork can be prepared automatically, but preparing and handing over a body cannot.
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.
Discussing and negotiating prearranged funerals with clients
staying humanThis work happens in the physical world: prearranged funerals, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Discuss and negotiate prearranged funerals with clients.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (10–18 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: Selling a funeral in advance rests on a family trusting the person in front of 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 3/4 · how much data exists 2/4.
Managing funeral home operations, including the hiring, training or supervision of embalmers, funeral attendants or other staff
staying humanThis work happens in the physical world: funeral home operations, including the hiring, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Manage funeral home operations, including the hiring, training, or supervision of embalmers, funeral attendants, or other staff.” (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: Hiring, training and supervising funeral staff runs on relationships built in the building.
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.
Planning placement of caskets at funeral sites or placing or adjusting lights
staying humanThis work happens in the physical world: placement of caskets, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Plan placement of caskets at funeral sites or place or adjust lights, fixtures, or floral displays.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (0–13 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Placing caskets, lights and flowers at the funeral site is physical arranging in the room.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Participating in community activities for funeral home promotion or other purposes
staying humanThis work happens in the physical world: community activities, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Participate in community activities for funeral home promotion or other purposes.” (O*NET task statement)
How this row was scored
Exposure score: 4 out of 100 (0–11 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: Turning up at community events to represent the funeral home means being there in person.
The five ratings: output a model can produce 1/4 · 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 1/4.
Closing caskets and leading funeral corteges to churches or burial sites
staying humanThis work happens in the physical world: caskets, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Close caskets and lead funeral corteges to churches or burial sites.” (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: Closing caskets and leading a cortege means being there in person.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 1/4.
Performing embalming duties
staying humanThis work happens in the physical world: duties, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Perform embalming duties, as necessary.” (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: Embalming is hands-on work on a body.
The five ratings: output a model can produce 0/4 · 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 1/4.
Receiving or ushering people to their seats for services
staying humanThis work happens in the physical world: people, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Receive or usher people to their seats for services.” (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: Ushering mourners to their seats means being present at the service.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 0/4.
Cleaning funeral home facilities and grounds
staying humanThis work happens in the physical world: funeral home facilities, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Clean funeral home facilities and grounds.” (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: Cleaning the funeral home and grounds is physical work.
The five ratings: output a model can produce 0/4 · 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 0/4.
Removing deceased remains from place of death
staying humanThis work happens in the physical world: deceased remains, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Remove deceased remains from place of death.” (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: Collecting a body from where someone died means physically going and doing it.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 1/4.
What this job pays, and how many people do it
- Median pay
- $55,010a 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
- 25,100in 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: clergy members in, a record out. The rows above are exactly that shape: contacting cemeteries to schedule the opening and closing of graves and arranging for clergy members to perform needed services. What it cannot do is be answerable: the preparation needs a named person the rules will accept, and software cannot be that person. 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
Start with what does not change: overseeing the preparation and care of the remains of people is the middle of this job, and the evidence on this page says it stays with a person.
So, given all that: 14% of this job's task weight sits in rows the software is already learning, 14% in rows that change shape rather than disappear, and 72% in rows it is nowhere near. That is the position, measured across 22 scored tasks. It is not a forecast about you.
So the thing worth your attention is not the job going away. It is the layer around it. Contacting cemeteries to schedule the opening and closing of graves is the part turning into software, and being the person who understands that layer is worth money.
This week: one thing
Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to clergy members, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.
- What you end up holding
- a straight answer about what is actually being rolled out, and when
- How long it takes
- ten minutes
If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether the preparation is in scope or not. Nothing to log into, no license needed.
Over the next 90 days
Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near planning, scheduling or coordinating funerals, burials or cremations, arranging details. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.
Over the next 12 months
On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. 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 morticians, undertakers, and funeral arrangers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was funeral home managers: only about 32% of its durable work is work you already do. And on the numbers you do not need one. This job scores 23/100 here, with only 14% of the task list in the top band, and “obtain information needed to complete legal documents” is not work that hands over cleanly. None of them beats deepening what you already have.
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.
Funeral Home Managers
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “consult with families or friends of the deceased to arrange funeral details”. Across the whole of both lists that adds up to about 32% of the work in that job the software is not taking.
Why I am not recommending it: It is closer than most, and still not close enough: about 32% of that job's durable work is already yours, against the 35% I want to see before I will call something a route.
Funeral Attendants
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already arrange for pallbearers or inform pallbearers or honorary groups of their duties, and their equivalent is to act as pallbearers. Across both published task lists that is about 21% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 21% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. It is a pay cut, in those words: $35,680 against your $55,010, 35.1% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Embalmers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already remove deceased remains from place of death, and their equivalent is to remove the deceased from place of death and transport to funeral home. Across both published task lists that is about 17% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 17% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. And it is a narrow door: about 3,890 of those jobs against 25,100 of yours (OEWS May 2025), 15% 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: 14% of its task weight, across 22 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like overseeing the preparation and care of the remains of people arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
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 nearest United Kingdom equivalent is Undertakers, mortuary and crematorium assistants. It is a close match rather than an identical one: the two countries draw the boundary of the job in slightly different places.
Switch to the United Kingdom page →close match
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 morticians / undertakers / funeral arrangers, 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 14% 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 morticians / undertakers / funeral arrangers. 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 morticians / undertakers / funeral arrangers 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 Morticians, Undertakers, and Funeral Arrangers?
- Not as a job, but it is already doing parts of the work. Across the 22 official task statements scored for Morticians, Undertakers, and Funeral Arrangers (United States, SOC 39-4031), 14% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 23 out of 100 (range 19–29, band: low). 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 “Morticians, Undertakers, and Funeral Arrangers” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Maintain financial records, order merchandise, or prepare accounts” (66/100, high); “Contact cemeteries to schedule the opening and closing of graves” (64/100, high); “Arrange for clergy members to perform needed services” (64/100, 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 “Morticians, Undertakers, and Funeral Arrangers” stay human?
- About 72% 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: “Remove deceased remains from place of death” (0/100, minimal); “Clean funeral home facilities and grounds” (0/100, minimal); “Receive or usher people to their seats for services” (0/100, 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 “Morticians, Undertakers, and Funeral Arrangers” do about AI?
- Start from the ledger rather than the headline: 14% of this job's weighted core work is exposed, and roughly 72% 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 Morticians, Undertakers, and Funeral Arrangers 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 22 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
- 4 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.