Will AI replace IT quality and testing professionals?

Not as a job, but it is already doing parts of the work. Across the 56 official task statements scored for IT quality and testing professionals (United Kingdom, SOC 2136), 75% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 71 out of 100 (range 65–76, 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 “IT quality and testing professionals” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Create test scripts for automated testing” (93/100, very high); “Design test plans to outline testing procedures” (93/100, very high); “Monitor the performance of specific applications and software systems to ensure functionality” (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 “IT quality and testing professionals” stay human?

About 5% 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: “Conduct quality assurance checks to ensure product standards are met” (8/100, minimal); “Collaborate with cross-sector specialists and global colleagues to integrate their expertise into projects” (18/100, minimal); “Support staff in meeting project deadlines” (26/100, 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 “IT quality and testing professionals” do about AI?

Start from the ledger rather than the headline: 75% of this job's weighted core work is exposed, and roughly 5% 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 IT quality and testing professionals 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 56 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.

UK dataswitch to US

IT quality and testing professionals

conducting testing on various software applications to detect defects and ensure they are fit, communicating findings to technical and non-technical colleagues and providing input on functional requirements during product design reviews. If that's your week, this page is about your job.

The honest answer

Most tasks in this job are the kind AI has learned to do: creating test scripts for automated testing. The tasks, though, are not you.

Your move: three real directions from here ↓

Where the work sits, by task weight

shifting to AI: 75%
changing shape: 20%
staying human: 5%

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

Whole-job exposure score 71 out of 100 (65–76 allowing for uncertainty): high exposure, across 56 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 it quality and testing professionals 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.

It would be a lie to soften that, and another lie to promise a rebuilt version of this job inside this job.

So the hope here is what you already carry: the judgment you bring to quality assurance checks is real, and the moves below are built from it. The first step is down this page.

Your week, as this page understands it

IT quality and testing professionals test the quality of IT software, systems and computer games and identify and recommend solutions to problems and improvements that could be made. The job title says “it quality” or “testing professionals”: officially one job, two names. The real job is the part underneath: conducting quality assurance checks to ensure product standards are met. 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 it quality and testing professionals is not one task. It is 56 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is conducting quality assurance checks to ensure product standards are met, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 75%
changing shape: 20%
staying human: 5%

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

How we know this

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.

38 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.

Shifting to AI

42 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.

Conducting testing on various software applications to detect defects and ensure they are fit for purpose
This is reading one thing and writing another: various software applications in, a record out. That is the shape today's tools are built for.
importance 95 · 2136/00
Source: “Conduct testing on various software applications to detect defects and ensure they are fit for purpose.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Software testing is heavily automated already, with people deciding what the results mean.
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 4/4.
Carrying out manual and automated software tests to meet project deadlines
This is reading one thing and writing another: manual in, a record out. That is the shape today's tools are built for.
importance 95 · 2136/00
Source: “Carry out manual and automated software tests to meet project deadlines.” (UK task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): 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: Test scripts and much of the running are already automated, though someone must set up and judge results.
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.
Analysing data from tests to improve software quality and performance
This is reading one thing and writing another: data in, a record out. That is the shape today's tools are built for.
importance 90 · 2136/00
Source: “Analyse data from tests to improve software quality and performance.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Finding patterns in test results is data analysis, which software is very good at.
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 4/4.
Designing and implementing tests to evaluate product functionality at each development stage
This is reading one thing and writing another: tests in, a record out. That is the shape today's tools are built for.
importance 90 · 2136/00
Source: “Design and implement tests to evaluate product functionality at each development stage.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Test design and automation is heavily documented with abundant public examples, so software produces usable tests at each stage.
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 4/4.

Changing shape

11 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.

Conducting different software test types
The software now makes the first pass at different software test types, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 95 · 2136/00
Source: “Conduct different software test types including functional, non-functional, and structural testing.” (UK task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Many test types can be automated, but choosing and running the awkward ones still needs a tester.
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 0/4 · how much data exists 3/4.
Conducting manual tests
The software now makes the first pass at manual tests, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 90 · 2136/00
Source: “Conduct manual tests.” (UK task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Manual testing leans on a person's feel for what looks wrong when actually using the product.
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 0/4 · how much data exists 3/4.
Testing in different environments, web and mobile
The software now makes the first pass at different environments, web and mobile, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 90 · 2136/00
Source: “Test in different environments including web and mobile.” (UK task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 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: Web testing is all on screen, but real phones and tablets often have to be handled.
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 0/4 · how much data exists 3/4.

Staying human

3 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.

Conducting quality assurance checks to ensure product standards are met
This work happens in the physical world: quality assurance checks, in a real place. Software cannot follow it there.
importance 85 · 2136/00
Source: “Conduct quality assurance checks to ensure product standards are met.” (UK task statement)
How this row was scored
Exposure score: 8 out of 100 (1–15 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Checking that products meet standards means handling and examining them.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Collaborating with cross-sector specialists and global colleagues to integrate their expertise into projects
The value here is that a specific person handles cross-sector specialists and stands behind it. That is earned, not computed.
importance 75 · 2136/00
Source: “Collaborate with cross-sector specialists and global colleagues to integrate their expertise into projects.” (UK task statement)
How this row was scored
Exposure score: 18 out of 100 (14–22 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Bringing in other people’s expertise depends on the working relationships between them.
The five ratings: output a model can produce 1/4 · 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.
Supporting staff in meeting project deadlines
The value here is that a specific person handles staff and stands behind it. That is earned, not computed.
importance 70 · 2136/00
Source: “Support staff in meeting project deadlines.” (UK task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 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: Helping staff hit deadlines is about knowing who needs a nudge and who needs help.
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 2/4.

Show the other 46 tasks

Creating test scripts for automated testing
shifting to AI
This is reading one thing and writing another: test scripts in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Create test scripts for automated testing.” (UK 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: Writing automated test scripts is one of the things code-generating software does most reliably.
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.
Designing test plans to outline testing procedures
shifting to AI
This is reading one thing and writing another: test plans in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Design test plans to outline testing procedures.” (UK 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: Test plans follow standard structures software can produce from the requirements.
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 the performance of specific applications and software systems to ensure functionality
shifting to AI
This is reading one thing and writing another: the performance of specific applications in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Monitor the performance of specific applications and software systems to ensure functionality.” (UK 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: Watching application performance is already done continuously by monitoring software rather than a person.
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.
Reporting documented software defects to developers
shifting to AI
This is reading one thing and writing another: documented software defects in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Report documented software defects to developers.” (UK 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: Raising documented defects with developers is routine reporting the tools already handle.
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.
Creating databases of known test defects
shifting to AI
This is reading one thing and writing another: databases of known test defects in, a record out. That is the shape today's tools are built for.
importance 80 · 2136/00
Source: “Create databases of known test defects.” (UK 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: Building and maintaining a defect database is routine record-keeping software handles.
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.
Writing bug reports
shifting to AI
This is reading one thing and writing another: bug reports in, a record out. That is the shape today's tools are built for.
importance 80 · 2136/00
Source: “Write bug reports.” (UK 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: A bug report is a short, standard piece of writing produced from what the test showed.
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.
Updating automated test scripts to ensure currency
shifting to AI
This is reading one thing and writing another: automated test scripts in, a record out. That is the shape today's tools are built for.
importance 75 · 2136/00
Source: “Update automated test scripts to ensure currency.” (UK 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: Updating test scripts to match changes is exactly what code-generating tools are good at.
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.
Writing detailed reports on project progress for stakeholders
shifting to AI
This is reading one thing and writing another: detailed reports in, a record out. That is the shape today's tools are built for.
importance 75 · 2136/00
Source: “Write detailed reports on project progress for stakeholders.” (UK 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: Progress reports are written from information already recorded, which software does quickly and well.
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.
Analysing documents to understand their main themes and purposes
shifting to AI
This is reading one thing and writing another: documents in, a record out. That is the shape today's tools are built for.
importance 70 · 2136/00
Source: “Analyse documents to understand their main themes and purposes.” (UK 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: Reading documents and identifying their themes and purpose is core work for modern text software.
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.
Producing project plans to outline future work
shifting to AI
This is reading one thing and writing another: project plans in, a record out. That is the shape today's tools are built for.
importance 70 · 2136/00
Source: “Produce project plans to outline future work.” (UK 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: Project plans follow standard shapes, and software produces them from a short brief without much editing.
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 testing and evaluation procedures to ensure software quality
shifting to AI
This is reading one thing and writing another: evaluation procedures in, a record out. That is the shape today's tools are built for.
importance 90 · 2136/00
Source: “Develop testing and evaluation procedures to ensure software quality.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Testing procedures follow well-published practice that software can draft in detail.
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 4/4.
Evaluating and debuging software code to ensure functionality
shifting to AI
This is reading one thing and writing another: software code in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Evaluate and debug software code to ensure functionality.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Reading code and finding defects is one of the strongest current uses of these tools.
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 4/4.
Testing programmes for errors to ensure software reliability
shifting to AI
This is reading one thing and writing another: programmes in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Test programmes for errors to ensure software reliability.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Running tests for errors is largely automated already.
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 4/4.
Documenting testing procedures, methodologies or criteria
shifting to AI
This is reading one thing and writing another: procedures, methodologies or criteria in, a record out. That is the shape today's tools are built for.
importance 80 · 2136/00
Source: “Document testing procedures, methodologies, or criteria.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Test documentation follows well-known formats with plenty of public examples, so software drafts it to a usable standard.
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 4/4.
Reviewing software documentation to mitigate risks
shifting to AI
This is reading one thing and writing another: software documentation in, a record out. That is the shape today's tools are built for.
importance 75 · 2136/00
Source: “Review software documentation to mitigate risks.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (76–90 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: Reading documentation to spot risks is close reading that software does quickly.
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 4/4.
Responding to internal and external research enquiries
shifting to AI
This is reading one thing and writing another: internal and external research enquiries in, a record out. That is the shape today's tools are built for.
importance 70 · 2136/00
Source: “Respond to internal and external research enquiries.” (UK task statement)
How this row was scored
Exposure score: 79 out of 100 (75–83 allowing for uncertainty): 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: Answering research enquiries from documented sources is well suited to software.
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 3/4.
Carrying out stress, performance, functional and scalability testing
shifting to AI
This is reading one thing and writing another: stress, performance, functional and scalability in, a record out. That is the shape today's tools are built for.
importance 90 · 2136/00
Source: “Carry out stress, performance, functional, and scalability testing.” (UK 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: Performance and load tests are driven by tools, but shaping realistic tests needs knowledge of the system.
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.
Identifying and recording faults or 'bugs' so they
shifting to AI
This is reading one thing and writing another: faults in, a record out. That is the shape today's tools are built for.
importance 90 · 2136/00
Source: “Identify and record faults or 'bugs' so they can be fixed.” (UK task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): 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: Spotting a fault and writing it up clearly is a well-defined job that tools already assist heavily.
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.
Designing testing scenarios to simulate real-world
shifting to AI
This is reading one thing and writing another: scenarios in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Design testing scenarios to simulate real-world use.” (UK 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: Realistic test scenarios can be drafted, though they rely on knowing how the product is really used.
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.
Developing testing programmes for error or bug retests
shifting to AI
This is reading one thing and writing another: programmes in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Develop testing programmes for error or bug retests.” (UK 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: Retest programmes are built from existing defect records, so drafts come easily.
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.
Identifying and troubleshooting software issues to ensure product quality
shifting to AI
This is reading one thing and writing another: software issues in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Identify and troubleshoot software issues to ensure product quality.” (UK task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): 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: Tracing a software fault back to its cause is pattern work that current tools do well.
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.
Identifying problems with programme function
shifting to AI
This is reading one thing and writing another: problems in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Identify problems with programme function, output, online screen, or content.” (UK 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: Spotting where a programme misbehaves is pattern-matching software does well against logs and output.
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 programme performance to ensure efficient and problem-free operations
shifting to AI
This is reading one thing and writing another: programme performance in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Monitor programme performance to ensure efficient and problem-free operations.” (UK task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): 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: Performance monitoring runs automatically and raises alerts without a person watching.
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.
Specifying testing standards and procedures to assess product quality before market launch
shifting to AI
This is reading one thing and writing another: standards in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Specify testing standards and procedures to assess product quality before market launch.” (UK 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: Testing standards are documented practice software can draft for a manager to approve.
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.
Testing new systems for functionality and reliability
shifting to AI
This is reading one thing and writing another: new systems in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Test new systems for functionality and reliability.” (UK 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: A great deal of system testing is automated, though sign-off on whether it is fit for use stays 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 0/4 · how much data exists 3/4.
Testing system modifications to prepare for implementation
shifting to AI
This is reading one thing and writing another: system modifications in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Test system modifications to prepare for implementation.” (UK 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: Testing changes before release is largely automated, with people judging the results.
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.
Checking documentation for accuracy and completeness
shifting to AI
This is reading one thing and writing another: documentation in, a record out. That is the shape today's tools are built for.
importance 80 · 2136/00
Source: “Check documentation for accuracy and completeness.” (UK task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): 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: Checking documents for gaps and errors is a classic reading task, though accuracy needs product knowledge.
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.
Installing and configuring recreations of software production environments for software performance testing
shifting to AI
This is reading one thing and writing another: recreations of software production environments in, a record out. That is the shape today's tools are built for.
importance 80 · 2136/00
Source: “Install and configure recreations of software production environments for software performance testing.” (UK 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: Rebuilding test environments is scripted work software now does from configuration files.
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.
Planning test schedules according to project scope or delivery dates
shifting to AI
This is reading one thing and writing another: test schedules in, a record out. That is the shape today's tools are built for.
importance 80 · 2136/00
Source: “Plan test schedules according to project scope or delivery dates.” (UK 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: Test scheduling is planning work software can draft from the delivery dates.
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.
Using the organisation's software testing tools to identify and report software bugs
shifting to AI
This is reading one thing and writing another: the organisation's software testing tools in, a record out. That is the shape today's tools are built for.
importance 80 · 2136/00
Source: “Use the organisation's software testing tools to identify and report software bugs.” (UK task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): 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: Running the organisation's test tools and reporting bugs is largely automated work.
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.
Assessing specific operational risks and implementing mitigation strategies
shifting to AI
This is reading one thing and writing another: specific operational risks in, a record out. That is the shape today's tools are built for.
importance 75 · 2136/00
Source: “Assess specific operational risks and implement mitigation strategies.” (UK task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): 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: Assessing operational risk and setting out mitigations follows published methods software applies to a usable standard.
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.
Estimating the time and resources required to conduct specific tests
shifting to AI
This is reading one thing and writing another: the time in, a record out. That is the shape today's tools are built for.
importance 75 · 2136/00
Source: “Estimate the time and resources required to conduct specific tests.” (UK 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: Estimating test effort follows patterns from past projects that software can learn from.
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.
Maintaining software testing programmes to keep them up-to-date
shifting to AI
This is reading one thing and writing another: software testing programmes in, a record out. That is the shape today's tools are built for.
importance 75 · 2136/00
Source: “Maintain software testing programmes to keep them up-to-date.” (UK 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: Keeping test suites current is maintenance work software increasingly does itself.
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.
Collaborating with software developers to design and implement software solutions
shifting to AI
This is reading one thing and writing another: software developers in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Collaborate with software developers to design and implement software solutions.” (UK 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: Designing solutions with developers is mostly shared documents and code, with some back-and-forth discussion.
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.
Providing feedback and recommendations to developers on software usability and functionality
shifting to AI
This is reading one thing and writing another: feedback in, a record out. That is the shape today's tools are built for.
importance 85 · 2136/00
Source: “Provide feedback and recommendations to developers on software usability and functionality.” (UK 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: Usability feedback for developers can be drafted well, though it lands better from a colleague.
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.
Monitoring bug resolution efforts and tracking successes
shifting to AI
This is reading one thing and writing another: bug resolution efforts in, a record out. That is the shape today's tools are built for.
importance 80 · 2136/00
Source: “Monitor bug resolution efforts and track successes.” (UK task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 allowing for uncertainty): 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: Tracking bug progress and reporting on it is straightforward automated reporting.
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.
Offering insights on product designs
shifting to AI
This is reading one thing and writing another: insights in, a record out. That is the shape today's tools are built for.
importance 75 · 2136/00
Source: “Offer insights on product designs, schedules, and potential problems.” (UK 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: Written observations on design and schedules are easy to produce from project information.
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.
Carrying out resource planning
shifting to AI
This is reading one thing and writing another: resource in, a record out. That is the shape today's tools are built for.
importance 70 · 2136/00
Source: “Carry out resource planning.” (UK 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: Resource planning is scheduling work that planning tools already handle well.
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.
Communicating findings to technical and non-technical colleagues
changing shape
The software now makes the first pass at findings, 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 80 · 2136/00
Source: “Communicate findings to technical and non-technical colleagues.” (UK 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: Rewriting technical findings for different audiences is something software does well; delivering them still involves talking to colleagues.
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.
Presenting findings to software development teams for technical review
changing shape
The software now makes the first pass at findings, 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 80 · 2136/00
Source: “Present findings to software development teams for technical review.” (UK 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: The summary can be produced automatically, but the review discussion happens live with the team.
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.
Diagnosing problems with field staff or customers and recommending solutions
changing shape
The software now makes the first pass at problems, 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 75 · 2136/00
Source: “Diagnose problems with field staff or customers and recommend solutions.” (UK 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: Diagnosis can be guided by software, though field staff and customers explain problems best in conversation.
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.
Presenting findings to business user teams for operational alignment
changing shape
The software now makes the first pass at findings, 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 75 · 2136/00
Source: “Present findings to business user teams for operational alignment.” (UK 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: Business teams want a person in the room to explain what the findings mean for 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 3/4.
Working on several projects at the same time
changing shape
The software now makes the first pass at several projects, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 70 · 2136/00
Source: “Work on several projects at the same time, often for several different clients.” (UK task statement)
How this row was scored
Exposure score: 49 out of 100 (42–56 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Juggling several client projects at once is about managing your own time and people's expectations.
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 1/4 · how much data exists 3/4.
Conducting software compatibility tests with programmes and hardware
changing shape
The software now makes the first pass at software compatibility tests, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 90 · 2136/00
Source: “Conduct software compatibility tests with programmes and hardware.” (UK task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Compatibility testing is largely automated, but hardware combinations sometimes need physical rigs.
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 0/4 · how much data exists 3/4.
Providing input on functional requirements during product design reviews
changing shape
The software now makes the first pass at input, 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 80 · 2136/00
Source: “Provide input on functional requirements during product design reviews.” (UK task statement)
How this row was scored
Exposure score: 40 out of 100 (33–47 allowing for uncertainty): partial 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: Written input is easy to produce, but design reviews are discussions between the people building it.
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 2/4 · how much data exists 3/4.
Obtaining information on limitations or capabilities for data processing projects by speaking with data processing or project managers
changing shape
The software now makes the first pass at information, 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 70 · 2136/00
Source: “Obtain information on limitations or capabilities for data processing projects by speaking with data processing or project managers.” (UK task statement)
How this row was scored
Exposure score: 40 out of 100 (33–47 allowing for uncertainty): partial 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: Finding out what is actually possible means asking the managers who run the systems.
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 2/4 · how much data exists 3/4.

What this job pays, and how many people do it

Median pay: £47,100a year, before tax, the middle of the range, so half earn more and half earn less.ashe-t14, 2025 · ASHE 2025 provisional (reference April 2025)Provisional, because the ONS revises this figure in the autumn.
How we know this
Source: ashe-t14
Reference period: ASHE 2025 provisional (reference April 2025)
Rounding: Shown to the nearest £100. The exact published figure is in the downloadable dataset. We do not render pounds the survey cannot support.
People doing this job: 32,600in the UK, 2026.nomis-aps · Apr 2025-Mar 2026 (latest APS 12-month period)This headcount comes from a survey, not a census, so treat it as a good estimate rather than an exact count.

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: test scripts in, a record out. The rows above are exactly that shape: creating test scripts for automated testing and conducting testing on various software applications to detect defects and ensure they are fit. What it cannot do is be there in the room, and that is still where quality assurance checks get 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: creating test scripts for automated testing is work today's tools do quickly and cheaply, and that is not coming back.

So, given all that: 75% of this job's task weight sits in rows the software is already learning, 20% in rows that change shape rather than disappear, and 5% in rows it is nowhere near. That is the position, measured across 56 scored tasks. It is not a forecast about you.

What you have that the software does not is conducting quality assurance checks to ensure product standards are met, 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 test scripts 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 test scripts, 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 creating test scripts for automated testing” 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 conducting quality assurance checks to ensure product standards are met 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, spend an hour with National Careers Service. It is free and government-funded, 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 UK occupations to IT quality and testing professionals (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was IT technicians: only about 9% of its durable work is work you already do, it is under the same pressure this job is and it pays 25.2% less. I am not going to pretend that is comfortable news: 75% 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. “conduct different software test types” 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 412 UK 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.

IT technicians
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “conduct software compatibility tests with programmes and hardware”. Across the whole of both lists that adds up to about 9% of the work in that job the software is not taking.
Why I am not recommending it: Almost none of it is work you already do: about 9% of the durable side of that job. That is a different job, not a next step. I will not move you off one melting floe onto another: 60% of its own task list already scores in the top exposure band (61/100 in this release), so the same software is eating it. It is a pay cut, in those words: £35,259 against your £47,118, 25.2% less (ASHE Table 14.7a, 2025 provisional (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Computer system and equipment installers and servicers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already conduct software compatibility tests with programmes and hardware, and their equivalent is to conduct hardware or software tests to ensure system functionality. 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. It is a pay cut, in those words: £34,237 against your £47,118, 27.3% less (ASHE Table 14.7a, 2025 provisional (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Programmers and software development professionals
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “conduct software compatibility tests with programmes and hardware”. Across the whole of both lists that adds up to about 4% of the work in that job the software is not taking.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step. I will not move you off one melting floe onto another: 61% of its own task list already scores in the top exposure band (63/100 in this release), so the same software is eating it.
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: 75% of its task weight, across 56 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: conducting quality assurance checks to ensure product standards are met 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 Kingdom figures

The United States splits this work across more than one official group, of which Database Architects is the closest. The pay and employment figures are not directly comparable, and we do not average them together.

Switch to the United States page →partial match

The other groups this work is counted across:

In US official statistics this job is counted as Database Architects, Software Quality Assurance Analysts and Testers, Web and Digital Interface Designers and Computer Occupations, All Other. 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

Where to go next, and what it costs

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.

In England:
National Careers Service
A free hour with a government-funded careers adviser is worth more than another evening of reading. In England that's the National Careers Service.
Free, government-funded
- Discover your skills and careers (the skills assessment)
In England:
National Careers Service - Find a course
Search what's actually running near you before you spend anything.
Free to search; individual courses vary
In England:
Free courses for jobs (Level 3 qualifications)
A free Level 3 qualification you already qualify for beats a paid course you don't need.
Free for eligible adults
In England:
Skills Bootcamps
Free, up to 16 weeks, and you get a job interview at the end. In England these are Skills Bootcamps - search what's running near you.
Free for eligible adults in England
- Skills Bootcamps - what they are and who can do them (DfE, Skills for Careers)
- Skills Bootcamps - JobHelp (DWP)
In Scotland:
My World of Work (Skills Development Scotland)
In Scotland it's My World of Work, from Skills Development Scotland.
Free, publicly funded
- Skills Development Scotland
In Wales:
Careers Wales
In Wales it's Careers Wales.
Free, Welsh Government-funded
In Northern Ireland:
Careers Service Northern Ireland
In Northern Ireland it's the Careers Service on nidirect.
Free, Department for the Economy-funded

No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for it quality / testing professionals, and we are not going to point you at the nearest one and call it a fit.

There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 75% of the work on this page is already inside what they can do.

Try The AI Authority free →

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

The AI Authority is a general community about working with AI, not a course for it quality / testing professionals. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.

Noted, and thank you. We’ll email you if a Space for it quality / testing professionals launches. Nothing else.

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No Space for it quality / testing professionals yet. Should there be one?

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

Collab365 launches new communities where the need is real. If one for it quality / testing professionals existed, with researched problems, courses and people in the same boat, would you want in?

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This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.

Questions people ask about this job

Will AI replace IT quality and testing professionals?: Not as a job, but it is already doing parts of the work. Across the 56 official task statements scored for IT quality and testing professionals (United Kingdom, SOC 2136), 75% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 71 out of 100 (range 65–76, 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 “IT quality and testing professionals” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Create test scripts for automated testing” (93/100, very high); “Design test plans to outline testing procedures” (93/100, very high); “Monitor the performance of specific applications and software systems to ensure functionality” (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 “IT quality and testing professionals” stay human?: About 5% 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: “Conduct quality assurance checks to ensure product standards are met” (8/100, minimal); “Collaborate with cross-sector specialists and global colleagues to integrate their expertise into projects” (18/100, minimal); “Support staff in meeting project deadlines” (26/100, 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 “IT quality and testing professionals” do about AI?: Start from the ledger rather than the headline: 75% of this job's weighted core work is exposed, and roughly 5% 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 IT quality and testing professionals 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 56 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

About the data on this page

Provisional, because the ONS revises this figure in the autumn.
This headcount comes from a survey, not a census, so treat it as a good estimate rather than an exact count.
The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
38 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: gaisi-indexProcessing: catalogue-bridge → ssc-relatedness-weighting → task-scoring → score-aggregation
Task weights: gaisi-index (relatedness)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
Pay and employment: ashe-t14 (ASHE 2025 provisional (reference April 2025))nomis-aps (Apr 2025-Mar 2026 (latest APS 12-month period))

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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Using these figures?

Cite this

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 2026-08-05. 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.