Software Quality Assurance Analysts and Testers
In short: today's best AI models could do about 66% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 91% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 8% of the time, stays with people.
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.
186,740 people do this job in the US. $104,300 a year.
Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on4 h
- A person checks AI's work23 h
- Desk work AI can't do yet10 h
- Stays with people3 h
Software Quality Assurance Analysts and Testers, now: of a 40-hour week, AI could take on 4 hours, 23 hours become checking its work, 10 hours are desk work it can't do yet, and 3 hours stay with people.
The largest pieces: Design test plans and scripts (about 2 h, a person checks); Run software testing programs (about 2 h, a person checks); Develop testing programs (about 2 h, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 70%
- 22%
- 4%
- 4%
- 0%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 66% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 25%. Today's estimate: 66%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, 1.4% went to this job's tasks in May 2026, the 18th largest of the 447 jobs that showed up at all; 8 of its 30 tasks showed up. Within each of Anthropic's methods, never across a change: 5.4% to 4.5% (released February and March 2025); 5.9% to 6% (August 2025 to February 2026); 1.5% to 1.4% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 5.4% | 3 of 708 | 14 of 30 |
| Released March 2025 | 4.5% | 3 of 703 | 14 of 30 |
| The week of Aug 4, 2025 (released September 2025) | 5.9% | 1 of 655 | 11 of 30 |
| The week of Nov 13, 2025 (released January 2026) | 7.7% | 1 of 672 | 11 of 30 |
| The week of Feb 5, 2026 (released March 2026) | 6% | 1 of 677 | 11 of 30 |
| April 2026 (released June 2026) | 1.5% | 16 of 434 | 9 of 30 |
| May 2026 (released June 2026) | 1.4% | 18 of 447 | 8 of 30 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates almost none of this job's working time as physical work, so robots do not reach it.
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
8% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Visit beta sites, the in-person work, 4%
- Coordinate user and third-party testing, the conversation, 2%
- Give developers usability feedback, the conversation, 0.9%
What becomes checking the machine
81% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it. Another 11% is desk work that is small if wrong, which can be handed over with lighter checks.
- Develop testing programs, costly if wrong, 13%
- Develop automated testing tools, costly if wrong, 11%
- Design test plans and scripts, costly if wrong, 7%
- Run software testing programs, costly if wrong, 7%
- Document test procedures, costly if wrong, 5%
- Modify software to fix errors, costly if wrong, 4%
What to learn
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check: spotting what a draft gets wrong is a skill of its own.
- Briefing a model and checking its drafts. About 70% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
- Running AI inside the business systems. About 22% of the time is work inside business systems, which a model can do only once it is connected: knowing the systems well enough to set that up and watch it.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 30 tasks from .
| Task | ||||
|---|---|---|---|---|
| Develop testing programs that address areas such as database impacts, software scenarios, regression testing, negative testing, error or bug retests, or usability.Designing and writing the test programs.Done more than monthly by most who do it. | 13% | 1.3 work days3.3 h to 4.2 work days | Documents 100% | 44%Half by Dec 2026 |
| Design or develop automated testing tools.Designing and coding test automation tools.Done more than yearly by most who do it. AI observed on this task. | 11% | 2.5 work days6.7 h to 1.7 work weeks | Documents 100% | 18%Half by Jun 2027 |
| Design test plans, scenarios, scripts, or procedures.Writing test plans, scenarios and scripts.Done more than monthly by most who do it. | 7% | 3.3 h1.3 h to 1.7 work days | Documents 100% | 84%Half by now |
| Install, maintain, or use software testing programs.Installing and operating the testing tools.Done several times a day by most who do it. | 7% | 1.7 h25 min to 6.7 h | Systems 100% | 88%Half by now |
| Visit beta testing sites to evaluate software performance.Being at the customer's site to watch the software in use, with notes.Done yearly or less by most who do it. | 6% | 6.7 h3.3 h to 2.5 work days | In person 70%, documents 30% | 24%Desk part half by now |
| Document test procedures to ensure replicability and compliance with standards.Writing test procedures so they can be repeated.Done daily by most who do it. | 5% | 1.7 h25 min to 5 h | Documents 100% | 94%Half by now |
| Coordinate user or third-party testing.Calls and messages with testers outside the team, with the plan.Done more than yearly by most who do it. | 4% | 6.7 h1.7 h to 2.5 work days | Conversation 60%, documents 40% | 22%Desk part half by now |
| Modify existing software to correct errors, allow it to adapt to new hardware, or to improve its performance.Changing code to correct errors or improve performance. AI observed on this task. | 4% | 6.7 h1.7 h to 3.3 work days | Documents 100% | 46%Half by Dec 2026 |
| Identify, analyze, and document problems with program function, output, online screen, or content.Working out what is wrong with a function or screen and writing it up.Done several times a day by most who do it. | 4% | 38 min13 min to 2.5 h | Documents 100% | 100%Half by now |
| Monitor program performance to ensure efficient and problem-free operations.Watching the running software and its logs from a console.Done more than weekly by most who do it. | 4% | 1.3 h25 min to 3.3 h | Systems 100% | 99%Half by now |
| Conduct software compatibility tests with programs, hardware, operating systems, or network environments.Running the software on different systems and noting what fails.Done more than monthly by most who do it. | 4% | 3.3 h50 min to 1.3 work days | Systems 70%, documents 30% | 80%Half by now |
| Create or maintain databases of known test defects.Keeping the database of known defects up to date.Done daily by most who do it. | 3% | 1.3 h25 min to 2.5 h | Systems 100% | 100%Half by now |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Software Quality Assurance Analysts and Testers is within reach of AI now?
- An estimated 66% of the working time is within reach of AI models now and 91% by the end of 2028, on METR's long-run pace at four in five (87% to 92% across the three paces the site shows). Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Software Quality Assurance Analysts and Testers come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Design test plans and scripts (84% of the task's time now, 100% by the end of 2028); Run software testing programs (88% of the task's time now, 100% by the end of 2028); and Develop testing programs (44% of the task's time now, 100% by the end of 2028).
- Which tasks of Software Quality Assurance Analysts and Testers stay with people?
- Every task has a desk part, so each can come partly within reach; the conversation, in-person and hands-on parts of each task stay with people, about 8% of the working time.
- What should Software Quality Assurance Analysts and Testers learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are reviewing work you did not do yourself; briefing a model and checking its drafts; and running AI inside the business systems. By the end of 2028 on the long-run pace at four in five, about 8% of the working time stays with people, 81% becomes checking a model's work and 11% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Software Quality Assurance Analysts and Testers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 1.4% went to this job's tasks, the 18th largest share of the 447 jobs that showed up; 8 of its 30 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 52%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Software Quality Assurance Analysts and Testers?
- Anthropic's robot exposure rating (September 2026) finds almost none of the working time is physical work, so robots do not reach it.
- How is this estimated?
- From the 30 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on September 30, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
This job in your state or metro area
Embed these figures on your site
A small card with the share of working time within reach now and at the end of 2027, 2028 and 2030, the date and a link back. Free under CC BY 4.0; the card carries the credit.
Your own version of this job
The page above is the occupation. Your job is your title and what you actually do: give both, and they are read against these tasks in your browser, nothing sent anywhere. The headline is free: how much of your working time is within reach now and by the end of 2028, and how many of the tasks your description names.
The full personal report is $19, to print or save as a PDF: every task with when it comes within reach, which ones your description names, the parts of your description the task list does not cover, what stays with you, what becomes checking the machine and what to learn.