Professionals · code 2356

Information technology trainers

AI can write the training guide. Getting a nervous team to use the new system is still a trainer.

AI could take a fair chunk of half the six tasks, led by keeping up with new software and researching training material. Designing, running and reviewing the training are mostly out of its reach.

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

Information technology trainers develop, schedule and conduct training programmes and courses for computer and other information technology users outside the mainstream primary, secondary and higher education systems. Tasks include - (a) identifying the information technology training needs and requirements of individual users and organizations; (b) preparing and developing instructional training material and aids such as handbooks, visual aids, online tutorials, demonstration models and supporting training reference documentation; (c) designing, coordinating, scheduling and conducting training and development programmes that can be delivered in the form of individual and group instruction, and facilitating workshop meetings, demonstrations and conferences; (d) monitoring and performing ongoing evaluation and assessment of training quality and effectiveness, and reviewing and modifying training objectives, methods and course deliverables; (e) gathering, investigating and researching background materials to gain a full understanding of the subject matter and systems; (f) keeping up to date with new product version releases, advances in software and general information technology trends, writing end user products and materials such as user training, tutorial and instruction manuals, online help, and operating and maintenance instructions. Examples of the occupations classified here: - Computer trainer - Software trainer Some related occupations classified elsewhere: - University lecturer - 2310 - Vocational education teacher - 2320 - Secondary school teacher - 2330 - Primary school teacher - 2341 - Staff development officer - 2424

ICT trainer

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

53 / 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

362 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 6 tasks for how much of it AI could do. They average 47 out of 100, so it holds up at 100 − 47 = 53.

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?

Information technology trainers 53

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.

Writing guides and tutorials.
Researching new software.
Training materials.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

Running training sessions.
Supporting people who struggle.
Working out what people need.

Both

What's arriving

New work that only exists because the AI does.

Training people to use AI tools.
AI help built into software.
Digital skills 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 59, against an average of 47. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

59
Keeping up-to-date with new product version releases, advances in software, and general information technology trends, writing end user products and materials such as user training, tutorial and instruction manuals, online help, and operating and maintenance instructions.

Medium
56
Gathering, investigating and researching background materials to gain a full understanding of the subject matter and systems

Medium
53
Preparing and developing instructional training material and aids such as handbooks, visual aids, online tutorials, demonstration models, and supporting training reference documentation

Medium
42
Identifying the information technology training needs and requirements of individual users and organizations

Low
37
Monitoring and performing ongoing evaluation and assessment of training quality and effectiveness, and reviewing and modifying training objectives, methods and course deliverables

Low
36
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

6 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

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 IT trainers be worried?

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

Parts of it are exposed. Keeping up with releases, research and writing materials are rated Medium; identifying needs, evaluation and running programmes are Low. AI writes materials fast; teaching and support 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

None of the new jobs we've written up start from here yet. Could be you're the first. See the jobs AI is creating →

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 →