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Training and Development Specialists

presenting information with a variety of instructional techniques or formats, designing, planning and developing alternative training methods if expected improvements are not seen. If that's your week, this page is about your job.

The honest answer

This job is splitting in two: obtaining, organizing or developing training procedure manuals, guides or course materials, such as handouts or visual materials is work AI now does quickly and cheaply, and presenting information with a variety of instructional techniques or formats is work it can't touch.

Your move: what you can actually do about this ↓

Which half fills your week decides your exposure. That is more in your control than it sounds.

Your week, as this page understands it

Design or conduct work-related training and development programs to improve individual skills or organizational performance. May analyze organizational training needs or evaluate training effectiveness. The job title says “training” or “development specialists”: officially one job, two names. The real job is the part underneath: presenting information with a variety of instructional techniques or formats. 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 training and development specialists is not one task. It is 20 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is presenting information with a variety of instructional techniques or formats, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI
52%
changing shape
16%
staying human
32%

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

Whole-job exposure score 61 out of 100 (55–67 allowing for uncertainty): high exposure, across 20 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 training and development specialists 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.

Shifting to AI

10 tasks

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.

  • Obtaining, organizing or developing training procedure manuals, guides or course materials, such as handouts or visual materials

    This is reading one thing and writing another: procedure manuals, guides or course materials in, a record out. That is the shape today's tools are built for.

    importance 5 · Core
    Source: “Obtain, organize, or develop training procedure manuals, guides, or course materials, such as handouts or visual materials.” (O*NET task statement)
    How this row was scored

    Exposure score: 100 out of 100 (96–100 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: Writing manuals, guides and handouts from source material is exactly the kind of document production AI does to a high standard.

    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 0/4 · how much data exists 4/4.

  • Evaluating modes of training delivery

    This is reading one thing and writing another: modes of training delivery in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Evaluate modes of training delivery, such as in-person or virtual, to optimize training effectiveness, training costs, or environmental impacts.” (O*NET task statement)
    How this row was scored

    Exposure score: 75 out of 100 (68–82 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 delivery options on cost and effectiveness is a documented analysis AI can work through using the organisation's numbers.

    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.

  • Monitoring, evaluating or recording training activities or programing effectiveness

    This is reading one thing and writing another: activities in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Monitor, evaluate, or record training activities or program effectiveness.” (O*NET task statement)
    How this row was scored

    Exposure score: 93 out of 100 (86–100 allowing for uncertainty): very high exposure, medium confidence.

    Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.

    The rating behind it: Attendance, scores and feedback are captured automatically, so tracking and reporting on training effectiveness is largely a data task.

    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 0/4 · how much data exists 3/4.

  • Developing alternative training methods if expected improvements are not seen

    This is reading one thing and writing another: alternative training methods if expected improvements are not in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Develop alternative training methods if expected improvements are not seen.” (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: Coming up with a different way to teach something draws on well-documented methods.

    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

4 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.

  • Offering specific training programs to help workers maintain or improving job skills

    The software now makes the first pass at specific training programs, 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 · Core
    Source: “Offer specific training programs to help workers maintain or improve job skills.” (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: Programmes can be assembled and offered digitally, though matching them to individuals and getting take-up involves working with people.

    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.

  • Selecting and assigning instructors to conduct training

    The software now makes the first pass at instructors, 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 · Core
    Source: “Select and assign instructors to conduct training.” (O*NET task statement)
    How this row was scored

    Exposure score: 47 out of 100 (40–54 allowing for uncertainty): partial exposure, medium confidence.

    Why it sits in this group: reading one thing and writing another; the value is that a specific person does it.

    The rating behind it: Matching instructors to courses by availability and subject is schedulable, but judging who teaches well comes from knowing them.

    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 2/4.

  • Developing or implementing training programs

    The software now makes the first pass at programs, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.

    importance 3 · Supplemental
    Source: “Develop or implement training programs related to efficiency, recycling, or other issues with environmental impacts.” (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: Environmental training content is widely documented and easy to draft, though rolling it out across a workplace involves people.

    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.

Staying human

6 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.

  • Presenting information with a variety of instructional techniques or formats

    This work happens in the physical world: information, in a real place. Software cannot follow it there.

    importance 5 · Core
    Source: “Present information with a variety of instructional techniques or formats, such as role playing, simulations, team exercises, group discussions, videos, or lectures.” (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: Content and videos can be produced automatically, but running role plays and group discussion with learners is a facilitator's job.

    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.

  • Designing, planning, organizing or directing orientation and training programs for employees or customers

    The value here is that a specific person handles orientation and stands behind it. That is earned, not computed.

    importance 4 · Core
    Source: “Design, plan, organize, or direct orientation and training programs for employees or customers.” (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: Curriculum design is drafting work AI does well, but organising and running a live programme means coordinating real people.

    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.

  • Assessing training needs through surveys

    The value here is that a specific person handles needs and stands behind it. That is earned, not computed.

    importance 4 · Core
    Source: “Assess training needs through surveys, interviews with employees, focus groups, or consultation with managers, instructors, or customer representatives.” (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: Surveys and their analysis are easy to automate, but people speak more openly about skill gaps in conversation with a colleague.

    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.

Show the other 10 tasks

  • Keeping up with developments in area of expertise by reading current journals

    shifting to AI

    This is reading one thing and writing another: with developments in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Keep up with developments in area of expertise by reading current journals, books, or magazine articles.” (O*NET task statement)
    How this row was scored

    Exposure score: 100 out of 100 (93–100 allowing for uncertainty): very high exposure, medium confidence.

    Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.

    The rating behind it: Journals and articles are published text, and AI can read and summarise them faster than a person keeping up manually.

    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 0/4 · how much data exists 4/4.

  • Scheduling classes based on availability of classrooms

    shifting to AI

    This is reading one thing and writing another: classes in, a record out. That is the shape today's tools are built for.

    importance 3 · Core
    Source: “Schedule classes based on availability of classrooms, equipment, or instructors.” (O*NET task statement)
    How this row was scored

    Exposure score: 93 out of 100 (89–97 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: Timetabling around room, equipment and instructor availability is a scheduling problem software solves well from booking data.

    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 0/4 · how much data exists 3/4.

  • Monitoring training costs and preparing budget reports to justify expenditures

    shifting to AI

    This is reading one thing and writing another: costs in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Monitor training costs and prepare budget reports to justify expenditures.” (O*NET task statement)
    How this row was scored

    Exposure score: 93 out of 100 (89–97 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: Training spend is tracked in finance systems, so producing budget reports and cost justifications is routine report generation.

    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 0/4 · how much data exists 3/4.

  • Evaluating training materials

    shifting to AI

    This is reading one thing and writing another: materials in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Evaluate training materials prepared by instructors, such as outlines, text, or handouts.” (O*NET task statement)
    How this row was scored

    Exposure score: 85 out of 100 (81–89 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: Reviewing written training materials for clarity, accuracy and coverage is document work AI does quickly and consistently.

    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 4/4.

  • Coordinating recruitment and placement of training program participants

    shifting to AI

    This is reading one thing and writing another: recruitment in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Coordinate recruitment and placement of training program participants.” (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: Signing people up, matching them to courses and handling the scheduling is administrative work systems already manage.

    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.

  • Devising programs to develop executive potential among employees in lower-level positions

    shifting to AI

    This is reading one thing and writing another: programs in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Devise programs to develop executive potential among employees in lower-level positions.” (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: Leadership development approaches are widely documented, so a solid programme design can be drafted and then tailored locally.

    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.

  • Referring trainees to employer relations representatives

    changing shape

    The software now makes the first pass at trainees, 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 3 · Supplemental
    Source: “Refer trainees to employer relations representatives, to locations offering job placement assistance, or to appropriate social services agencies, if warranted.” (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: Available services are listed and easy to match to a person's situation, though a sensitive referral suits someone they know.

    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.

  • Attending meetings or seminars to obtain information for use in training programs or to inform management of training program status

    staying human

    The value here is that a specific person handles meetings and stands behind it. That is earned, not computed.

    importance 4 · Core
    Source: “Attend meetings or seminars to obtain information for use in training programs or to inform management of training program status.” (O*NET task statement)
    How this row was scored

    Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low 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: Status updates can be written automatically, but taking part in meetings and briefing managers face to face is a person's role.

    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 3/4.

  • Supervising, evaluating or referring instructors to skill development classes

    staying human

    The value here is that a specific person handles instructors and stands behind it. That is earned, not computed.

    importance 3 · Core
    Source: “Supervise, evaluate, or refer instructors to skill development classes.” (O*NET task statement)
    How this row was scored

    Exposure score: 28 out of 100 (21–35 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: Development suggestions can be generated, but supervising and appraising instructors rests on a working relationship with each of 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 3/4 · how much data exists 2/4.

  • Negotiating contracts with clients for desired training outcomes

    staying human

    The value here is that a specific person handles contracts and stands behind it. That is earned, not computed.

    importance 3 · Core
    Source: “Negotiate contracts with clients for desired training outcomes, fees, or expenses.” (O*NET task statement)
    How this row was scored

    Exposure score: 24 out of 100 (17–31 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: Contract drafts are easy to produce, but agreeing fees and outcomes with a client is a live negotiation between people.

    The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.

What this job pays, and how many people do it

Median pay
$69,280a 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
458,300in 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: procedure manuals, guides or course materials in, a record out. The rows above are exactly that shape: obtaining, organizing or developing training procedure manuals, guides or course materials and evaluating modes of training delivery. What it cannot do is be there in the room, and that is still where information 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

The exposed part of your job is the biggest part, and I am not going to dress that up: obtaining, organizing or developing training procedure manuals, guides or course materials is work today's tools do quickly and cheaply, and that is not coming back.

So, given all that: 52% of this job's task weight sits in rows the software is already learning, 16% in rows that change shape rather than disappear, and 32% in rows it is nowhere near. That is the position, measured across 20 scored tasks. It is not a forecast about you.

What you have that the software does not is presenting information with a variety of instructional techniques or formats, plus the years of knowing when something looks wrong before you can say why. That is the raw material for everything below.

This week: one thing

Sit on the machine's side of the desk. Pick one real piece of procedure manuals, guides or course materials you would normally do yourself, let whatever software you already have take the first pass at it, and then go through what it produced and write down every single thing it got wrong. One evening this week. Do not fix anything yet. Just catch it.

What you end up holding
a written list of the machine’s mistakes, in your handwriting
How long it takes
an evening, or an hour if you pick one job rather than one client

If you can’t run software on your employer’s or your clients’ data: Do the same hunt on paper. Take one printed piece of procedure manuals, guides or course materials, work through it the way you always do, and mark every point where you made a call rather than followed a rule. Same evening, same list, nothing to log into and nobody to ask permission from. That list is the same artifact: it is the judgment written down.

Over the next 90 days

Change one sentence about what you do. Not on a CV. Out loud, to whoever pays you. From “my job is obtaining, organizing or developing training procedure manuals, guides or course materials, such as handouts or visual materials” to “I check what the software does and tell you what it means.” Your error list from this week is what makes that sentence true instead of a claim, so use it: show it once, to one person, inside the next ninety days. Same skills, priced as judgment rather than as typing.

Over the next 12 months

Walk toward the end of this job that answers for things, and get it recognised. Pick the one part of presenting information with a variety of instructional techniques or formats you are already best at, and spend the year making it formal: a qualification, a named responsibility, a specialism people ask for by name. Price it honestly: that is evenings, it is months rather than weeks, and the seats are competitive because everyone in your position is looking at the same door. 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 training and development specialists (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was training and development managers: only about 6% of its durable work is work you already do and there are far fewer of those jobs than of yours. I am not going to pretend that is comfortable news: 52% of your own task list is already in the top exposure band. But the answer on this evidence is not a sideways jump into a job with the same problem. It is to walk toward the end of this one that answers for things. “present information with a variety of instructional techniques or formats” is the part that stays with a person, and spending a year getting formally recognised for it beats a standing start somewhere else.

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.

  • Training and Development Managers

    Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already select and assign instructors to conduct training, and their equivalent is to train instructors and supervisors in techniques and skills for training and dealing with…. Across both published task lists that is about 6% of the durable work in that job.

    Why I am not recommending it: Almost none of it is work you already do: about 6% of the durable side of that job. That is a different job, not a next step. And it is a narrow door: about 48,050 of those jobs against 458,300 of yours (OEWS May 2025), 10% as many seats.

    Look at that job’s page anyway →

  • Compensation, Benefits, and Job Analysis Specialists

    Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already assess training needs through surveys, interviews with employees, focus groups, or consultation with…, and their equivalent is to observe, interview, and survey employees and conduct focus group meetings to collect job…. Across both published task lists that is about 6% of the durable work in that job.

    Why I am not recommending it: Almost none of it is work you already do: about 6% of the durable side of that job. That is a different job, not a next step. And it is a narrow door: about 112,380 of those jobs against 458,300 of yours (OEWS May 2025), 25% as many seats.

    Look at that job’s page anyway →

  • Career/Technical Education Teachers, Postsecondary

    Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already monitor, evaluate, or record training activities or program effectiveness, and their equivalent is to administer oral, written, or performance tests to measure progress and to evaluate training…. Across both published task lists that is about 5% of the durable work in that job.

    Why I am not recommending it: Almost none of it is work you already do: about 5% of the durable side of that job. That is a different job, not a next step. And it is a narrow door: about 114,110 of those jobs against 458,300 of yours (OEWS May 2025), 25% as many seats.

    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: 52% of its task weight, across 20 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.

  • “It’s too late for me to become something else”

    You are not starting from zero, and the page shows why: presenting information with a variety of instructional techniques or formats is work the software cannot do and you already do it. The move above is a repricing of what you know, not a new career. Nobody who has just left college has that.

  • “I should learn to code”

    Almost certainly not. The value in your job is moving toward checking, deciding and answering for the output, not toward writing the software. A weekend of Python will not change your position; the error list from this week will.

  • 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 Other vocational and industrial trainers 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 Other vocational and industrial trainers and Information technology trainers. 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

Two honest options, and no deadline on either

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.

A nearby route

There's no Space built for training and development specialists yet.

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

The closest match is Microsoft Copilot Adopters, a community for the people who have to make Microsoft 365 Copilot actually useful in Word, Excel, Outlook and Teams. It overlaps with the part of your job that is growing: helping colleagues get real work out of Microsoft 365 Copilot, and setting the review habits around AI-assisted output. It only applies where your employer has Copilot. If that overlap isn't you, the free route below covers the same ground.

Try Microsoft Copilot Adopters free →

7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.

After the trial it is a paid community, and you get identical data either way. If the overlap above is not your job, the moves above cost nothing and stand on their own.

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Questions people ask about this job

Will AI replace Training and Development Specialists?
Not as a job, but it is already doing parts of the work. Across the 20 official task statements scored for Training and Development Specialists (United States, SOC 13-1151), 52% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 61 out of 100 (range 55–67, band: high). 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 “Training and Development Specialists” can AI already do?
The highest-scoring tasks in release 2026-q4.1 are: “Keep up with developments in area of expertise by reading current journals, books, or magazine articles” (100/100, very high); “Obtain, organize, or develop training procedure manuals, guides, or course materials, such as handouts or visual materials” (100/100, very high); “Schedule classes based on availability of classrooms, equipment, or instructors” (93/100, very 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 “Training and Development Specialists” stay human?
About 32% 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: “Present information with a variety of instructional techniques or formats, such as role playing, simulations, team exercises, group discussions, videos, or l…” (20/100, low); “Negotiate contracts with clients for desired training outcomes, fees, or expenses” (24/100, low); “Supervise, evaluate, or refer instructors to skill development classes” (28/100, low). 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 “Training and Development Specialists” do about AI?
Start from the ledger rather than the headline: 52% of this job's weighted core work is exposed, and roughly 32% 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 Training and Development Specialists 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 20 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

Where these numbers come from

Worth knowing about these figures

  • The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
  • 2 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 2026-08-04.
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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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 . 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.