US dataswitch to UK
Software Quality Assurance Analysts and Testers
identifying, analyzing, developing or specifying standards and updating automated test scripts to ensure currency. 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: documenting software defects, using a bug tracking system and reporting defects to software developers. The tasks, though, are not you.
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 beta testing sites is real, and the moves below are built from it. The first step is down this page.
Your week, as this page understands it
Develop and execute software tests to identify software problems and their causes. Test system modifications to prepare for implementation. Document software and application defects using a bug tracking system and report defects to software or web developers. Create and maintain databases of known defects. May participate in software design reviews to provide input on functional requirements, operational characteristics, product designs, and schedules. The job title says “software quality assurance analysts” or “testers”: officially one job, two names. The real job is the part underneath: visiting beta testing sites to evaluate software performance. 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 software quality assurance analysts and testers is not one task. It is 30 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is visiting beta testing sites to evaluate software performance, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 78%
- changing shape
- 16%
- staying human
- 5%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 67 out of 100 (61–73 allowing for uncertainty): high exposure, across 30 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 software quality assurance analysts and testers 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.
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.
- One row is marked low confidence, so treat it as a ballpark rather than a fine measurement.
- 6 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
23 tasksTasks 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.
Identifying, analyzing and documenting problems with program function, output, online screen or content
This is reading one thing and writing another: problems in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Identify, analyze, and document problems with program function, output, online screen, or content.” (O*NET 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: Finding and writing up faults in software output is close to what automated testing and analysis tools already do.
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.
Documenting software defects, using a bug tracking system and reporting defects to software developers
This is reading one thing and writing another: software defects in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Document software defects, using a bug tracking system, and report defects to software developers.” (O*NET 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: Writing a clear defect report into a tracker is standard, well-structured writing software does reliably.
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.
Developing testing programs that address areas
This is reading one thing and writing another: programs in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Develop testing programs that address areas such as database impacts, software scenarios, regression testing, negative testing, error or bug retests, or usability.” (O*NET 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 programs are code, and generating code from a described scenario is a core strength of current 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 3/4.
Designing test plans, scenarios, scripts or procedures
This is reading one thing and writing another: test plans, scenarios, scripts or procedures in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Design test plans, scenarios, scripts, or procedures.” (O*NET 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 plans and scripts follow documented patterns, so software drafts them quickly from the requirements.
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.
Changing shape
5 tasksTasks 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.
Installing, maintaining or using software testing programs
The software now makes the first pass at software testing programs, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Install, maintain, or use software testing programs.” (O*NET 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: Setting up and running test tooling is partly configuration in specific environments someone has to maintain.
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.
Participating in product design reviews to provide input on functional requirements
The software now makes the first pass at product design reviews, 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 4 · CoreSource: “Participate in product design reviews to provide input on functional requirements, product designs, schedules, or potential problems.” (O*NET 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: Design reviews are live discussions where input carries weight because of who gives 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.
Conducting software compatibility tests with programs
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 4 · CoreSource: “Conduct software compatibility tests with programs, hardware, operating systems, or network environments.” (O*NET 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: Compatibility testing across hardware and operating systems needs those real environments available to run against.
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.
Coordinating user or third-party testing
The software now makes the first pass at user, 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 3 · CoreSource: “Coordinate user or third-party testing.” (O*NET 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: Coordinating other people testing runs on chasing and agreeing with them.
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.
Staying human
2 tasksTasks 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.
Visiting beta testing sites to evaluate software performance
This work happens in the physical world: beta testing sites, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Visit beta testing sites to evaluate software performance.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Visiting a beta testing site means physically being there.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Collaborating with field staff or customers to evaluate or diagnose problems and recommend possible solutions
The value here is that a specific person handles field staff and stands behind it. That is earned, not computed.
importance 3 · CoreSource: “Collaborate with field staff or customers to evaluate or diagnose problems and recommend possible solutions.” (O*NET task statement)
How this row was scored
Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low 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: Diagnosing a problem alongside field staff or customers depends on a live back-and-forth.
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 3/4.
Show the other 20 tasks
Updating automated test scripts to ensure currency
shifting to AIThis 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 4 · CoreSource: “Update automated test scripts to ensure currency.” (O*NET 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.
Identifying program deviance from standards
shifting to AIThis is reading one thing and writing another: program deviance in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Identify program deviance from standards, and suggest modifications to ensure compliance.” (O*NET 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: Comparing code against documented standards is a check software performs quickly and consistently.
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 or developing automated testing tools
shifting to AIThis is reading one thing and writing another: automated testing tools in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Design or develop automated testing tools.” (O*NET 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: Building automated test tools is software development, which AI now assists 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 4/4.
Testing system modifications to prepare for implementation
shifting to AIThis is reading one thing and writing another: system modifications in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Test system modifications to prepare for implementation.” (O*NET 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.
Creating or maintaining databases of known test defects
shifting to AIThis 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 4 · CoreSource: “Create or maintain databases of known test defects.” (O*NET 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: Keeping a database of known defects current is by nature a software task.
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.
Reviewing software documentation to ensure technical accuracy
shifting to AIThis is reading one thing and writing another: software documentation in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Review software documentation to ensure technical accuracy, compliance, or completeness, or to mitigate risks.” (O*NET 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 documentation for accuracy and completeness is careful reading software does thoroughly.
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.
Documenting test procedures to ensure replicability and compliance with standards
shifting to AIThis is reading one thing and writing another: test procedures in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Document test procedures to ensure replicability and compliance with standards.” (O*NET 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: Writing down test procedures so others can repeat them is straightforward document 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.
Monitoring program performance to ensure efficient and problem-free operations
shifting to AIThis is reading one thing and writing another: program performance in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Monitor program performance to ensure efficient and problem-free operations.” (O*NET 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: Watching program performance for problems is continuous monitoring already handled by 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 3/4.
Installing and configuring recreations of software production environments to allow testing of software performance
shifting to AIThis 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 3 · CoreSource: “Install and configure recreations of software production environments to allow testing of software performance.” (O*NET 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: Recreating a production environment for testing is largely scripted, though it depends on that specific setup.
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.
Performing initial debugging procedures by reviewing configuration files
shifting to AIThis is reading one thing and writing another: initial debugging procedures in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Perform initial debugging procedures by reviewing configuration files, logs, or code pieces to determine breakdown source.” (O*NET 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: Reading logs and configuration files to find where something broke is well suited to current 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 3/4.
Conducting historical analyses of test results
shifting to AIThis is reading one thing and writing another: historical analyses of test results in, a record out. That is the shape today's tools are built for.
importance 3 · CoreSource: “Conduct historical analyses of test results.” (O*NET 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: Analyzing past test results is straightforward data analysis.
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.
Modifying existing software to correct errors
shifting to AIThis is reading one thing and writing another: software in, a record out. That is the shape today's tools are built for.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Modify existing software to correct errors, allow it to adapt to new hardware, or to improve its performance.” (O*NET 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: Fixing errors and improving performance in existing code is something AI does well given access to the codebase.
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.
Storing, retrieving and manipulating data for analysis of system capabilities and requirements
shifting to AIThis is reading one thing and writing another: data in, a record out. That is the shape today's tools are built for.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Store, retrieve, and manipulate data for analysis of system capabilities and requirements.” (O*NET 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: Pulling and reshaping data to answer questions about a system suits software, though deciding what to examine needs judgement.
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.
Evaluating or recommending software for testing or bug tracking
shifting to AIThis is reading one thing and writing another: software in, a record out. That is the shape today's tools are built for.
importance 3 · CoreSource: “Evaluate or recommend software for testing or bug tracking.” (O*NET task statement)
How this row was scored
Exposure score: 70 out of 100 (63–77 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: Comparing testing and tracking tools is documented research, though the choice gets agreed 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 1/4 · how much data exists 4/4.
Monitoring bug resolution efforts and tracking successes
shifting to AIThis 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 4 · CoreSource: “Monitor bug resolution efforts and track successes.” (O*NET 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.
Planning test schedules or strategies in accordance with project scope or delivery dates
shifting to AIThis is reading one thing and writing another: test schedules in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Plan test schedules or strategies in accordance with project scope or delivery dates.” (O*NET 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: Test schedules can be drafted from scope and delivery dates, though the plan gets negotiated with the project.
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.
Developing or specifying standards, methods or procedures to determine product quality or release readiness
shifting to AIThis is reading one thing and writing another: standards, methods or procedures in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Develop or specify standards, methods, or procedures to determine product quality or release readiness.” (O*NET 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: Quality standards can be drafted from published practice, but the release bar gets agreed 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 1/4 · how much data exists 3/4.
Investigating customer problems referred by technical support
shifting to AIThis is reading one thing and writing another: customer problems in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Investigate customer problems referred by technical support.” (O*NET 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: Investigating a reported customer problem is analysis work, though it involves going back to the customer.
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 AIThis is reading one thing and writing another: feedback in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Provide feedback and recommendations to developers on software usability and functionality.” (O*NET 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.
Recommending purchase of equipment to control dust
changing shapeThe software now makes the first pass at purchase of equipment, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Recommend purchase of equipment to control dust, temperature, or humidity in area of system installation.” (O*NET task statement)
How this row was scored
Exposure score: 51 out of 100 (39–63 allowing for uncertainty): partial exposure, low confidence.
Why it sits in this group: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: Recommending dust and climate equipment is documented specification work with some judgment about the actual room.
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 2/4.
What this job pays, and how many people do it
- Median pay
- $104,300a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
- People doing this job
- 186,740in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)
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: software defects in, a record out. The rows above are exactly that shape: documenting software defects and identifying, analyzing. What it cannot do is be there in the room, and that is still where beta testing sites 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: documenting software defects, using a bug tracking system and reporting defects to software developers is work today's tools do quickly and cheaply, and that is not coming back.
So, given all that: 78% of this job's task weight sits in rows the software is already learning, 16% in rows that change shape rather than disappear, and 5% in rows it is nowhere near. That is the position, measured across 30 scored tasks. It is not a forecast about you.
What you have that the software does not is visiting beta testing sites to evaluate software performance, 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 software defects 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 software defects, 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 documenting software defects, using a bug tracking system and reporting defects to software developers” 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 visiting beta testing sites to evaluate software performance 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, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, 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 US occupations to software quality assurance analysts and testers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was network and computer systems administrators: only about 7% of its durable work is work you already do and it is under the same pressure this job is. I am not going to pretend that is comfortable news: 78% 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. “install, maintain, or use software testing programs” 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 830 US 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.
Network and Computer Systems Administrators
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 programs, hardware, operating systems, or network environments, and their equivalent is to design, configure, and test computer hardware, networking software and operating system software. Across both published task lists that is about 7% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 7% 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: 65% of its own task list already scores in the top exposure band (60/100 in this release), so the same software is eating it.
Computer Network Support Specialists
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 programs, hardware, operating systems, or network environments, and their equivalent is to install new hardware or software systems or components, ensuring integration with existing network…. Across both published task lists that is about 5% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 5% 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: 66% of its own task list already scores in the top exposure band (66/100 in this release), so the same software is eating it. It is a pay cut, in those words: $76,220 against your $104,300, 26.9% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Computer Occupations, All Other
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 programs, hardware, operating systems, or network environments, and their equivalent is to direct the installation of operating systems, network or application software, or computer or…. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% 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: 70% of its own task list already scores in the top exposure band (66/100 in this release), so the same software is eating it.
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: 78% of its task weight, across 30 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: visiting beta testing sites to evaluate software performance 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 States figures
The United Kingdom splits this work across more than one official group, of which Cyber security professionals is the closest. The pay and employment figures are not directly comparable, and we do not average them together.
Switch to the United Kingdom page →partial match
The other groups this work is counted across:
In UK official statistics this job is counted as Cyber security professionals, IT quality and testing professionals and Programmers and software development professionals. 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.
Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
Free
No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for software quality assurance analysts / testers, 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 78% of the work on this page is already inside what they can do.
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 software quality assurance analysts / testers. 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 software quality assurance analysts / testers launches. Nothing else.
That did not look like an email address, so nothing was saved. Have another go below.
We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.
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 Software Quality Assurance Analysts and Testers?
- Not as a job, but it is already doing parts of the work. Across the 30 official task statements scored for Software Quality Assurance Analysts and Testers (United States, SOC 15-1253), 78% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 67 out of 100 (range 61–73, 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 “Software Quality Assurance Analysts and Testers” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Update automated test scripts to ensure currency” (93/100, very high); “Document software defects, using a bug tracking system, and report defects to software developers” (83/100, very high); “Identify program deviance from standards, and suggest modifications to ensure compliance” (83/100, 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 “Software Quality Assurance Analysts and Testers” 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: “Visit beta testing sites to evaluate software performance” (0/100, minimal); “Collaborate with field staff or customers to evaluate or diagnose problems and recommend possible solutions” (30/100, low); “Coordinate user or third-party testing” (40/100, partial). 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 “Software Quality Assurance Analysts and Testers” do about AI?
- Start from the ledger rather than the headline: 78% 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 Software Quality Assurance Analysts and Testers 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 30 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
- One row is marked low confidence, so treat it as a ballpark rather than a fine measurement.
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 6 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
- onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
- Task weights
- onet-db (im-rt-with-imputed)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
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.
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}
}Data as of release 2026-q4.1, published . 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.