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Professionals · code 2424

Training and staff development professionals

AI can build the training course. Getting people to change what they do is still training.

Digging up background material is the one task AI could take a fair chunk of. Writing training materials, spotting needs and evaluating courses are mostly out of its reach.

What they actually do (and what else they get called)

Training and staff development professionals plan, develop, implement and evaluate training and development programmes to ensure management and staff acquire the skills and develop the competencies required by organizations to meet organizational objectives. Tasks include - (a) identifying training needs and requirements of individuals and organizations; (b) setting human resource development objectives and evaluating learning outcomes; (c) preparing and developing instructional training material and aids such as handbooks, visual aids, online tutorials, demonstration models and supporting training reference documentation; (d) designing, coordinating, scheduling and conducting training and development programmes that can be delivered in the form of individual and group instruction, and facilitating workshops, meetings, demonstrations and conferences; (e) liaising with external training providers to arrange delivery of specific training and development programmes; (f) promoting internal and external training and development, and evaluating these promotional activities; (g) monitoring and performing ongoing evaluation and assessment of internal and external training quality and effectiveness, and reviewing and modifying training objectives, methods and course deliverables; (h) gathering, investigating and researching background materials to gain an understanding of various subject matters and systems. Examples of the occupations classified here: - Staff development officer - Training officer - Workforce development specialist

  • business coach
  • corporate trainer
  • corporate training manager

Job titles from the EU's ESCO list. Search for any of them on the jobs page and you'll end up here.

59 / 100

Changing significantly

AI could do a real share of the everyday tasks. The job is changing shape, not vanishing.

Not the odds you keep your job. It's how much of the everyday work still needs a person, out of 100.

← Robot's turf Human's turf →

The ILO's official verdict: Exposed: Gradient 2

330 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 8 tasks for how much of it AI could do. They average 40.7 out of 100, so it holds up at 100 − 40.7 = 59.3.

That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Exposed: Gradient 2”: A good share of the tasks are affected.

This job rates 19.3 out of 100 for how hands-on it is. The score above only looks at AI tools, not robots, but for work this far from the physical that matters less.

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

Man v Bot · compare

Who holds up better?

Training and staff development professionals 59

v

Go on, try your partner's job. Or your sibling's. We won't tell.

Man v Bot

Where the bot helps, and where the human wins

Bot

What AI takes

The routine stuff. You may not miss it.

  • Researching and writing training materials.
  • E-learning content.
  • Evaluating results.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Running workshops and coaching.
  • Understanding what people need.
  • Changing behaviour, not just knowledge.

Both

What's arriving

New work that only exists because the AI does.

  • Teaching staff to use AI.
  • AI tutors and personalised learning.
  • Reskilling programmes.

Written by a human, from the ILO's task ratings below. Yes, we see the irony. Read it as one person's take.

Meet your two rivals

They're not the same machine. AI software can only reach the parts of a job done on a screen or in words. A chatbot can't climb a ladder. A robot might, one day, if it doesn't fall off.

The AI

Lives in a screen. Never had to fix a boiler.

Threat level: Medium

57 could do without you

It could take over some of the work, and help with more. It could help with 76 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Lower

19 how hands-on

Not much of this job needs hands, so the robot can sit this one out.

So could a robot do the physical part?

Less than half of this job is hands-on. Robots still matter, but for a smaller part of the work, so we don't sort it any further.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 6 out of 100. The higher it is, the longer the robot waits.

19 How
hands-on
6 How fiddly
and cramped

Kind of hands-on work Less than half hands-on

The small print

They aren't a robot score, and nothing on this page is. Nobody measures how far robots have got well enough to put a number on it. These are the closest thing we have: how hands-on the job is, and how much fiddly, cramped work it takes, which is what Frey and Osborne found hardest for machines.

From O*NET, matched to one US job .

finger skill 16 · hand skill 0 · cramped spaces 3.2 · averaged · rule: hands-on under 50

estimated O*NET 31.0 BLS occupational crosswalk chain ISCO-08 to 2010 SOC (Aug 2012, rev. Jun 2015); 2010 to 2018 SOC (Nov 2017); O*NET-SOC 2019 taxonomy data 0.8-observed-use measures chosen by Frey & Osborne (2017) · the grouping is a sorting, not a measurement

The job, task by task

Every job is really a bundle of tasks. Here's this one unpacked, with how much of each AI could do, out of 100. The score is the average, and averages can hide a lot.

AI's favourite task here scores 61, against an average of 41. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 61

    Gathering, investigating and researching background materials to gain an understanding of various subject matters and systems.

    Medium
  2. 49

    Preparing and developing instructional training material and aids such as handbooks, visual aids, online tutorials, demonstration models and supporting training reference documentation

    Low
  3. 38

    Promoting internal and external training and development, and evaluating these promotional activities

    Low
  4. 37

    Designing, coordinating, scheduling and conducting training and development programmes that can be delivered in the form of individual and group instruction, and facilitating workshops, meetings, demonstrations and conferences

    Low
  5. 37

    Setting human resource development objectives and evaluating learning outcomes

    Low
  6. 35

    Liaising with external training providers to arrange delivery of specific training and development programmes

    Low
  7. 35

    Identifying training needs and requirements of individuals and organizations

    Low
  8. 35

    Monitoring and performing ongoing evaluation and assessment of internal and external training quality and effectiveness, and reviewing and modifying training objectives, methods and course deliverables

    Low

8 tasks · the High to Very Low labels are the ILO's

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

Sidekick or replacement?

A tool that makes you faster is a very different thing from one that does the task while you watch. Jobs and Skills Australia measured the two separately, which is handy.

AI helps you
76
AI does it for you
57

Sidekick wins, by 19 points.

How good a match is this?

One Australian job matches this one closely, so this is about as reliable as it gets here.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.8-observed-use matched to Australian jobs 2233

Meanwhile, in real life…

Everything else here is about what AI could do. This is what people actually did. When they asked Claude for help with this kind of work, did they hand the whole task over, or roll their sleeves up and work through it together?

Out of every 100 conversations

52
48

worked through it together handed it over

The small print

Anthropic publishes this about its own product, and it doesn't feed into any score here. These are people who use Claude, not workers in general, so little use here doesn't mean AI can't reach the job. This job makes up 0.13% of the conversations.

These two add up to 100. The bars elsewhere on the page don't, because each is scored on its own, so we don't put them side by side.

observed use Anthropic Economic Index release 2026-06-26, period beginning 2026-05-01 data 0.8-observed-use 2026-05-01 · Anthropic, about its own product

So, should trainers and learning professionals be worried?

Short answer: not worried, but paying attention. The job is changing.

Parts of it are changing. Researching material is rated Medium; writing materials, promotion, running programmes, setting objectives, working with providers, identifying needs and evaluating training are Low. AI makes course creation much faster; delivery and coaching stay human.

Worth remembering: we score tasks, not jobs. When AI takes on a task, the job usually reshuffles around it rather than vanishing.

Where this job could lead

How are the neighbours doing?

There are 92 jobs in the “Professionals” family, averaging 61. This one is below the family average.

Pit this against any other job →