Professionals · code 2512
Software developers
AI can write a lot of the code. Knowing what to build is still a developer.
AI could take a fair chunk of six of the eight tasks, led by testing, working out requirements and documenting fixes. Only talking things through with engineers and customers is mostly out of its reach.
What they actually do (and what else they get called)
Software developers research, analyse and evaluate requirements for existing or new software applications and operating systems, and design, develop, test and maintain software solutions to meet these requirements. Tasks include - (a) researching, analysing and evaluating requirements for software applications and operating systems; (b) researching, designing and developing computer software systems; (c) consulting with engineering staff to evaluate interfaces between hardware and software; (d) developing and directing software testing and validation procedures; (e) modifying existing software to correct errors, to adapt it to new hardware or to upgrade interfaces and improve performance; (f) directing software programming and development of documentation; (g) assessing, developing, upgrading and documenting maintenance procedures for operating systems, communications environments and applications software; (h) consulting with customers concerning maintenance of software systems. Examples of the occupations classified here: - Programmer analyst - Software designer - Software developer - Software engineer Some related occupations classified elsewhere: - Applications programmers - 2514
- software developer
- software architect
- user interface developer
- software analyst
Job titles from the EU's ESCO list. Search for any of them on the jobs page and you'll end up here.
47 / 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.
The ILO's official verdict: Exposed: Gradient 3
385 of 427 for holding up against AI
Not quite your week? Make it yours ↓
Why this score?
The ILO rated each of this job's 8 tasks for how much of it AI could do. They average 52.7 out of 100, so it holds up at 100 − 52.7 = 47.3.
That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Exposed: Gradient 3”: Most of the tasks are affected.
This job rates 11.6 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?
Software developers 47
vGo 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 and fixing code.
- Tests and documentation.
- Maintenance and upgrades.
Man
What people still do better
Judgement, trust and skilled hands. Hard to download.
- Deciding what to build.
- Reviewing AI-written code.
- System design and trade-offs.
Both
What's arriving
New work that only exists because the AI does.
- Working with AI coding agents.
- Building AI products.
- AI safety and evaluation.
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: High
63 could do without you
It could take over a lot of this job on its own. It could help with 77 of 100.
The robot
The wildcard. Has hands, still working out stairs.
How much it matters here: Lower
12 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 17 out of 100. The higher it is, the longer the robot waits.
hands-on
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, averaged across 2 US jobs .
finger skill 22.3 · hand skill 19.8 · cramped spaces 7.3 · 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 66, against an average of 53. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.
- 66
Developing and directing software testing and validation procedures
Medium - 61
Researching, analysing and evaluating requirements for software applications and operating systems
Medium - 53
Assessing, developing, upgrading and documenting maintenance procedures for operating systems, communications environments and applications software
Medium - 52
Directing software programming and development of documentation
Medium - 50
Researching, designing, and developing computer software systems
Medium - 50
Modifying existing software to correct errors, to adapt it to new hardware or to upgrade interfaces and improve performance
Medium - 45
Consulting with engineering staff to evaluate interfaces between hardware and software
Low - 45
Consulting with customers concerning maintenance of software system.
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
New · the weekly task audit
Your week, your score
The score above assumes software developers spend the same time on every task. You don't. Slide each task to how much of your week it takes, and we'll re-weight the same ILO ratings to fit your job.
- Some
- Some
- Some
- Some
- Some
- Some
- Some
- Some
Your score
47 / 100
Same as the job as a whole, so far.
Move the sliders to make it yours.
The job as a whole: 47 / 100
Link copied.
Nothing you enter leaves your browser. The link just carries your slider positions.
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
- 77
- AI does it for you
- 63
Sidekick wins, by 14 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 2613
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 1.67% of the conversations.
The data is sorted by US job, and this one matches 2 of them. We've combined them, counting each by how often it comes up in the conversations, so the busiest one counts most.
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 software developers be worried?
Short answer: not worried, but paying attention. The job is changing.
Parts of the job are changing fast. Testing, requirements, maintenance, documentation, design and fixing code are rated Medium; consulting engineers and customers is Low. AI coding tools are good and improving, so work shifts to design, review and judgement.
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
-
Forward deployed engineer A software engineer who moves in with the customer and stays until the AI actually works. Think house guest who also fixes the wiring. → -
AI red teamer Paid to break AI systems before someone with worse intentions does. Getting a chatbot to misbehave is, at last, a career. →
How are the neighbours doing?
There are 92 jobs in the “Professionals” family, averaging 62. This one is below the family average.
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- Secondary education teachers 70
- Midwifery professionals 70
- Civil engineers 70
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- Judges 69
- Electrical engineers 69
A closer look
There is a written profile for a job in this group.