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Technicians and associate professionals · code 3421

Athletes and sports players

AI can analyse your opponent. It can't run the race for you.

AI barely touches five of the eight tasks, including actually competing. Promo work, media interviews and planning tactics with coaches are mostly out of its reach too.

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

Athletes and sport players participate in competitive sporting events. They train and compete, either individually or as part of a team, in their chosen sport. Tasks include - (a) participating in competitive sporting events; (b) participating in regular practice and training sessions and undertaking private training to maintain the required standard of fitness and skill; (c) undertaking sports promotional activities and media interviews; (d) maintaining a high degree of expertise in a particular sport; (e) deciding on strategies in consultation with coaches; (f) assessing other competitors and conditions at venues; (g) competing in sporting events; (h) adhering to the rules and regulations associated with a specific sport. Examples of the occupations classified here: - Athlete - Bicycle racer - Boxer - Chess player - Footballer - Golfer - Hockey player - Jockey - Poker player - Racing driver - Skier - Tennis player - Wrestler

  • professional athlete

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

77 / 100

Mostly holds up against AI

AI can take a few chores off your plate, but most of the day is still yours.

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: Not Exposed

178 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 22.8 out of 100, so it holds up at 100 − 22.8 = 77.2.

That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Not Exposed”: None of this job's tasks scored high enough to count.

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

Pinch of salt: this number is probably too rosy

It only asks what AI software could do, and this job is 60 out of 100 hands-on. A chatbot can't do that part. A robot might, one day, and nobody measures how close that is.

Man v Bot · compare

Who holds up better?

Athletes and sports players 77

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.

  • Performance data and video analysis.
  • Media and promotional content.
  • Training plans from wearables.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Competing.
  • Training and physical preparation.
  • Performing under pressure.

Both

What's arriving

New work that only exists because the AI does.

  • AI-assisted training and injury prevention.
  • Building a personal brand online.
  • Data rights over performance tracking.

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: Low

19 could do without you

It could take over very little of the work on its own. It could help with 53 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

60 how hands-on

A fair part of this job is hands-on, so robots would be needed for that part, not just software.

So could a robot do the physical part?

Less fine handwork and fewer cramped spaces than a typical hands-on job. That clears one hurdle for machines. It doesn't mean machines are doing this work yet.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 35 out of 100. The higher it is, the longer the robot waits.

60 How
hands-on
35 How fiddly
and cramped

Kind of hands-on work Hands-on, less fiddly work

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 42.9 · hand skill 46.4 · cramped spaces 15.5 · averaged · rule: hands-on 50+ · fiddly under 39.4

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 40, against an average of 23. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 40

    Undertaking sports promotional activities and media interviews

    Low
  2. 34

    Deciding on strategies in consultation with coaches

    Low
  3. 25

    Maintaining a high degree of expertise in a particular sport

    Low
  4. 24

    Assessing other competitors and conditions at venues

    Very Low
  5. 24

    Adhering to the rules and regulations associated with a specific sport.

    Very Low
  6. 22

    Participating in regular practice and training sessions and undertaking private training to maintain the required standard of fitness and skill

    Very Low
  7. 8

    Participating in competitive sporting events

    Very Low
  8. 7

    Competing in sporting events

    Very 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
53
AI does it for you
19

Sidekick wins, by 34 points.

How good a match is this?

One Australian job matches, but only partly: not everyone in it does this job. Treat the numbers as a rough guide.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.8-observed-use matched to Australian jobs 4524

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?

Tiny sample alert This job makes up under 0.01% of all the conversations: a tiny slice, mostly the paperwork rather than the work. People using AI for a job isn't the same as AI being able to do it.

Out of every 100 conversations

53
47

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.

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 professional athletes be worried?

Short answer: not much. Some of the chores will change, and good riddance.

No. Media work, strategy and keeping up expertise are the most exposed tasks, all Low; training and competing rate Very Low. AI analysis and wearables are changing how athletes train and prepare, not who competes.

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 82 jobs in the “Technicians and associate professionals” family, averaging 65. This one is above the family average.

Pit this against any other job →