Will AI replace Funeral Attendants?

Not as a job, but it is already doing parts of the work. Across the 24 official task statements scored for Funeral Attendants (United States, SOC 39-4021), 2% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 6 out of 100 (range 5–11, band: minimal). 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 “Funeral Attendants” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Prepare obituaries for newspapers” (79/100, high); “Perform various administrative tasks, such as typing documents or answering telephone calls” (48/100, partial); “Obtain burial permits and register deaths” (42/100, partial). 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 “Funeral Attendants” stay human?

About 90% 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: “Embalm, dress, cosmeticize, and casket the deceased” (0/100, minimal); “Perform general maintenance tasks for funeral homes, such as maintaining equipment or caring for funeral grounds” (0/100, minimal); “Deliver floral arrangements or other items to family members of the deceased” (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 “Funeral Attendants” do about AI?

Start from the ledger rather than the headline: 2% of this job's weighted core work is exposed, and roughly 90% 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 Funeral Attendants 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 24 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.

US dataswitch to UK

Funeral Attendants

embalming dress, cosmeticize and casket, closing caskets at appropriate point in services and attending to the needs. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: greeting people at the funeral home is work software can't reach.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 2%
changing shape: 8%
staying human: 90%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 6 out of 100 (5–11 allowing for uncertainty): minimal exposure, across 24 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 funeral attendants 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.

What shifts is preparing obituaries for newspapers. This page scores what today's tools actually do, not headlines.

Your week, as this page understands it

Perform a variety of tasks during funeral, such as placing casket in parlor or chapel prior to service, arranging floral offerings or lights around casket, directing or escorting mourners, closing casket, and issuing and storing funeral equipment. The job title says “funeral attendants”. The real job is the part underneath: greeting people at the funeral home. 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 funeral attendants is not one task. It is 24 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is greeting people at the funeral home, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 2%
changing shape: 8%
staying human: 90%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

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.

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

1 task

Tasks 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 obituaries for newspapers
This is reading one thing and writing another: obituaries in, a record out. That is the shape today's tools are built for.
importance 5 · Supplemental
Source: “Prepare obituaries for newspapers.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (72–86 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: Obituaries follow a well-known pattern, so software writes a good draft once the family supplies the details.
The five ratings: output a model can produce 4/4 · 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

3 tasks

Tasks 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.

Performing various administrative tasks, such as typing documents or answering telephone calls
The software now makes the first pass at various administrative tasks, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Supplemental
Source: “Perform various administrative tasks, such as typing documents or answering telephone calls.” (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: Typing documents and answering the phone is general office work that software already handles much of.
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.
Obtaining doctors' signatures on death certificate and completing other paperwork
The software now makes the first pass at doctors' signatures, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · Supplemental
Source: “Obtain doctors' signatures on death certificate and complete other paperwork, such as insurance claims forms.” (O*NET task statement)
How this row was scored
Exposure score: 42 out of 100 (35–49 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: Chasing signatures and completing insurance forms is routine paperwork that software drafts and tracks well.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Obtaining burial permits and registering deaths
The software now makes the first pass at burial permits, 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 5 · Supplemental
Source: “Obtain burial permits and register deaths.” (O*NET task statement)
How this row was scored
Exposure score: 42 out of 100 (35–49 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; someone qualified has to answer for it.
The rating behind it: Permits and death registrations are standard forms, though a licensed funeral director normally has to be the one filing them.
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 0/4 · how much data exists 3/4.

Staying human

20 tasks

Tasks 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.

Greeting people at the funeral home
This work happens in the physical world: people, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Greet people at the funeral home.” (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: Greeting families arriving at a funeral home is about a person being there to meet them.
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 3/4 · how much data exists 1/4.
Performing a variety of tasks during funerals to assist funeral directors and to ensure that services run smoothly
This work happens in the physical world: a variety of tasks during funerals, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Perform a variety of tasks during funerals to assist funeral directors and to ensure that services run smoothly and as planned.” (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: Assisting at a live funeral service means physically being present and doing things as the service unfolds.
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 2/4 · how much data exists 1/4.
Directing or escorting mourners to parlors or chapels in which wakes or funerals are being held
This work happens in the physical world: mourners, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Direct or escort mourners to parlors or chapels in which wakes or funerals are being held.” (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: Escorting mourners to the right chapel requires a person walking with them.
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 3/4 · how much data exists 1/4.
Placing caskets in parlors or chapels prior to wakes or funerals
This work happens in the physical world: caskets, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Place caskets in parlors or chapels prior to wakes or funerals.” (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: Moving and positioning caskets in a chapel is heavy 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 1/4.
Arranging floral offerings or lights around caskets
This work happens in the physical world: floral offerings, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Arrange floral offerings or lights around caskets.” (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: Arranging flowers and lights around a casket is physical arranging done in the room.
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.
Closing caskets at appropriate point in services
This work happens in the physical world: caskets, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Close caskets at appropriate point in 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: Closing a casket at the right moment in a service is a physical act performed in the room.
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.

Show the other 14 tasks

Providing advice to mourners on how to make charitable donations in honor
staying human
This work happens in the physical world: advice, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Provide advice to mourners on how to make charitable donations in honor of the deceased.” (O*NET task statement)
How this row was scored
Exposure score: 21 out of 100 (14–28 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: The donation guidance itself is easy to write, but families usually want it explained gently by a person in the room.
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 3/4 · how much data exists 3/4.
Attending to the needs
staying human
This work happens in the physical world: the needs, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Attend to the needs of the bereaved, such as by offering comfort, counseling, or after-care programs.” (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 value is that a specific person does it.
The rating behind it: Comforting the recently bereaved works because a real person is present with them.
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 2/4.
Offering assistance to mourners as they enter or exit limousines
staying human
This work happens in the physical world: assistance, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Offer assistance to mourners as they enter or exit limousines.” (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: Helping mourners in and out of limousines means offering a real arm at the curbside.
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 3/4 · how much data exists 1/4.
Cleaning and driving funeral vehicles
staying human
This work happens in the physical world: funeral vehicles, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean and drive funeral vehicles, such as cars or hearses, in funeral processions.” (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: Washing and driving a hearse in a procession is entirely 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 1/4.
Carrying flowers to hearses or limousines for transportation to places of interment
staying human
This work happens in the physical world: flowers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Carry flowers to hearses or limousines for transportation to places of interment.” (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: Carrying flowers out to a hearse is manual handling.
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.
Cleaning funeral parlors or chapels
staying human
This work happens in the physical world: funeral parlors, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean funeral parlors or chapels.” (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 parlors and chapels is hands-on work in the rooms themselves.
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.
Issuing and storing funeral equipment
staying human
This work happens in the physical world: funeral equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Issue and store funeral equipment.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–7 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Issuing and putting away funeral equipment involves physically handling and storing the items.
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 2/4.
Assisting with cremations and the processing and packaging of cremated remains
staying human
This work happens in the physical world: cremations, in a real place. Software cannot follow it there.
importance 5 · Supplemental
Source: “Assist with cremations and the processing and packaging of cremated remains.” (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: Operating a cremator and handling remains is physical work carried out at the crematory.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Acting as pallbearers
staying human
This work happens in the physical world: pallbearers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Act as pallbearers.” (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: Carrying a casket as a pallbearer is physical work no software can take on.
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 2/4 · how much data exists 0/4.
Transporting the deceased to the funeral home
staying human
This work happens in the physical world: this work, in a real place. Software cannot follow it there.
importance 5 · Supplemental
Source: “Transport the deceased to the funeral home.” (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 and transporting a body to the funeral home is physical work requiring a vehicle and hands.
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.
Supervising funeral processions and assisting with cemetery parking
staying human
This work happens in the physical world: funeral processions, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Supervise funeral processions and assist with cemetery parking.” (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: Marshalling a procession and directing parking at a cemetery needs someone standing there 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 2/4 · how much data exists 1/4.
Delivering floral arrangements or other items to family members
staying human
This work happens in the physical world: floral arrangements, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Deliver floral arrangements or other items to family members of the deceased.” (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: Delivering flowers to a family home means physically taking them there.
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 2/4 · how much data exists 1/4.
Performing general maintenance tasks for funeral homes
staying human
This work happens in the physical world: general maintenance tasks, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Perform general maintenance tasks for funeral homes, such as maintaining equipment or caring for funeral 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: Maintaining buildings and grounds is hands-on practical work at the premises.
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.
Embalming dress, cosmeticize and casket
staying human
This work happens in the physical world: dress, cosmeticize and casket, in a real place. Software cannot follow it there.
importance 5 · Supplemental
Source: “Embalm, dress, cosmeticize, and casket the deceased.” (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; someone qualified has to answer for it.
The rating behind it: Embalming, dressing and casketing a body is skilled physical work on the deceased.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 2/4 · 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: $35,680a 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: 31,090in 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: various administrative tasks in, a record out. The rows above are exactly that shape: preparing obituaries for newspapers and performing various administrative tasks. What it cannot do is be there in the room, and that is still where people 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

Start with what does not change: greeting people at the funeral home is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 2% of this job's task weight sits in rows the software is already learning, 8% in rows that change shape rather than disappear, and 90% in rows it is nowhere near. That is the position, measured across 24 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. Preparing obituaries for newspapers 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 various administrative tasks, 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 a variety of tasks during funerals 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 performing various administrative tasks, such as typing documents or answering telephone calls. 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 funeral attendants (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was morticians, undertakers, and funeral arrangers: only about 19% of its durable work is work you already do. And on the numbers you do not need one. This job scores 6/100 here, with only 2% of the task list in the top band, and “greet people at the funeral home” 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.

Morticians, Undertakers, and Funeral Arrangers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already arrange floral offerings or lights around caskets, and their equivalent is to plan placement of caskets at funeral sites or place or adjust lights, fixtures…. Across both published task lists that is about 19% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 19% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →
Embalmers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already transport the deceased to the funeral home, 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 16% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 16% 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 31,090 of yours (OEWS May 2025), 13% as many seats.
Look at that job’s page anyway →
Funeral Home Managers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already perform a variety of tasks during funerals to assist funeral directors and to…, and their equivalent is to sell funeral services, products, or merchandise to clients. Across both published task lists that is about 12% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 12% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. The pay gap is the market pricing a barrier: $78,790 against your $35,680 is 2.21× (OEWS May 2025 (both)), and you would be crossing it holding about 12% of their durable work. A gap that size with an overlap that small is a wish, not a route.
Look at that job’s page anyway →

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: 2% of its task weight, across 24 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 greeting people at the funeral home 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:
American Job Center locator
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
- CareerOneStop local help hub
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
CareerOneStop
Free

Why there is no community here

Collab365, who build this site, run paid Spaces for a small number of subjects, and none of them is built for this job. We are not going to point you at the nearest one and call it a fit.

So the free services listed on this page are the whole answer, and it is the same answer we would give a friend.

Noted, and thank you. We’ll email you if a Space for funeral attendants 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 Space for funeral attendants yet. Should there be one?

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

What a Space actually is, in full

Collab365 launches new communities where the need is real. If one for funeral attendants existed, with researched problems, courses and people in the same boat, would you want in?

Your email

We use your email address for one thing: to tell you if a Space for funeral attendants launches. We never sell it, never use it for unrelated marketing, and every email has a one-click unsubscribe. Our privacy policy has the full version.

This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

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 Funeral Attendants?: Not as a job, but it is already doing parts of the work. Across the 24 official task statements scored for Funeral Attendants (United States, SOC 39-4021), 2% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 6 out of 100 (range 5–11, band: minimal). 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 “Funeral Attendants” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Prepare obituaries for newspapers” (79/100, high); “Perform various administrative tasks, such as typing documents or answering telephone calls” (48/100, partial); “Obtain burial permits and register deaths” (42/100, partial). 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 “Funeral Attendants” stay human?: About 90% 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: “Embalm, dress, cosmeticize, and casket the deceased” (0/100, minimal); “Perform general maintenance tasks for funeral homes, such as maintaining equipment or caring for funeral grounds” (0/100, minimal); “Deliver floral arrangements or other items to family members of the deceased” (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 “Funeral Attendants” do about AI?: Start from the ledger rather than the headline: 2% of this job's weighted core work is exposed, and roughly 90% 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 Funeral Attendants 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 24 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

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.

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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}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. 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.